Science Washing in Digital Health: How to Communicate Evidence Responsibly
Science washing in digital health is becoming an increasing concern as companies seek to build credibility while accelerating growth. The term refers to the use of scientific language or selective evidence to suggest a level of confidence in a product that is inaccurate, overstated, or not yet established. In digital health, this rarely involves fabricated data. More often, it reflects claims that extend beyond what available evidence genuinely supports.
How can digital health companies use science to build credibility without overstating evidence? This article explores how to communicate data responsibly while supporting growth.
What Is Science Washing?
Science washing refers to the use of scientific language or selective evidence to suggest a level of confidence in a product that is inaccurate, overstated, or not yet established. It is used across many industries (food, skincare, and digital health…) as a marketing tactic to increase customer confidence and, ultimately, sales. In digital health, science washing rarely looks like fabricated data; it is more often a matter of overstating data i.e. claiming more than the data shows.
How Science Washing Shows Up in Practice
A common example in digital health is wellbeing products making mental health claims such as “improves mood” or “lowers anxiety” without sufficient evidence. Another form of science washing occurs when wearables claim to measure a physiological state by indirectly inferring it from another signal, without demonstrating adequate validation for that inference. Similarly, machine learning models are sometimes promoted as “99% accurate” without context on how the metric was calculated, which dataset was used, or what limitations apply.
Science washing also appears in how evidence is described. Products are sometimes labelled “evidence-based” simply because they have a peer-reviewed publication, even when that study was a small pilot not designed to measure effectiveness, or was intended only to assess safety, tolerability, or engagement. Pilot studies, early safety work, and exploratory research all have real value. The problem arises when claims extend beyond what the science actually supports. Companies may also selectively report outcomes that present results in a more favourable light. As a result, website messaging can often appear far more optimistic than the underlying research actually supports.
The Risks of Science Washing
Digital health products are often used by vulnerable people seeking support. Overpromising what a product can deliver may divert users away from more appropriate or effective support. Using strong unproven claims is a marketing tactic that prioritizes short term gain over long term gain. Users who don’t see the effects they were promised will end up leaving the product and might discourage others from using it.
Regulators also warn against science-washing; both the MHRA and FDA look beyond formal documentation, and assess how products are described on websites, user communications, and also how they are actually used in the real world:
FDA’s general wellness guidance : “Products are not general wellness products if their labelling, advertising, user interface, or functionality includes any of the following: 1. references to specific diseases, clinical conditions, or diagnostic thresholds;…”
MHRA’s Digital Mental Health Technologies Guidance : “It is the manufacturer's responsibility to ensure that the intended purpose is clearly and consistently defined and communicated to potential users and other stakeholders in the labelling, instructions for use (IFU) and promotional materials (e.g. websites, social media and adverts) and technical documentation.”
Overstated claims can therefore trigger regulatory scrutiny if positioning drifts into medical territory without sufficient evidence. Whether a product is considered a wellness or a medical device is largely judged based on its claims - what you say your product does, how it helps, and who it helps. Positioning within the wellness space does not mean you cannot use science; it means your scientific framing must reflect your wellness status i.e. no clinical claims, no symptom-improvement claims, and no disease-related outcomes.
The collapse of Theranos remains one of the clearest examples of how overstated scientific claims can erode trust across the healthcare ecosystem. The company promoted blood testing technology as transformative, despite limited validated evidence to substantiate those claims. When evidence is overstated or presented prematurely, it risks weakening confidence among clinicians, regulators, and payers, especially at a time when digital health and AI already face heightened scrutiny. Products that promise more than they can reliably deliver don’t just damage individual reputations, they undermine credibility and fuel scepticism across the sector as a whole.
How to Build Scientific Credibility Without Crossing into Science Washing
So how can you build scientific credibility without crossing the line into science washing? Scientific credibility does not come from avoiding science. It comes from using it proportionately and transparently. Here are a few practical tips:
1. Enlist scientific support to guide marketing language.
Scientific professionals can help define clear internal guidance on which words to avoid, which terms require strict evidence thresholds, and how certain claims should be framed depending on the strength of available data.
2. Match your claims to the level of evidence you actually have.
Align your claims with the strength of your available evidence. At the MVP stage, focus on usability, engagement, and feasibility rather than outcomes. As you progress, small pilot studies can signal safety or preliminary associations but not effectiveness, as they are not powered to test it. Larger studies can begin to support performance or outcome claims, while only well-designed clinical investigations should lead to clinical claims.
3. Stay within the guardrails of your data.
Scientific claims are only valid within the context in which they were studied. If your participants had low-to-moderate anxiety, you cannot claim benefits across all anxiety severity levels. If your study lacked a comparator arm or only compared against a waitlist, you cannot claim equivalence with the gold standard of care.
4. Separate “field evidence” from “product evidence.”
General evidence that supports the technique you use in your product demonstrates scientific plausibility (scientific validity), but it does not form clinical evidence for your specific product. If other AI models can read X-rays at 90% precision, that does not mean yours can. Your model needs to be independently validated to make such claims.
5. Align scientific communication with regulatory positioning.
If a product is framed as a wellness or lifestyle tool, avoid making disease-level or therapeutic claims that imply medical effectiveness. Scientific messaging should stay consistent with the intended use, evidence base, and regulatory status to prevent confusion and reduce the risk of overstated claims.
6. Be transparent about your current level of evidence.
Transparency about what is known and what is still being explored builds long-term credibility. Phrases such as “early findings suggest…” or “currently being evaluated…” demonstrate scientific integrity without undermining growth.
Responsible scientific communication in digital health is about being accurate and precise, without overselling or underselling your findings. When evidence is communicated in this way, it strengthens credibility, supports responsible innovation, and builds trust with users, clinicians, and regulators. As the sector continues to grow, companies that communicate their science transparently will be better positioned for sustainable adoption.
If your company is navigating complex scientific or regulatory pathways for a digital health product, Hardian Health can help. Get in touch to discover how our expertise can support your journey from concept to clearance.
