Why We Can’t Expect the Same Level of Impact from Healthcare Messaging vs. Other Industries

Table of Contents

• A Quiet Explosion
• Lesson 1 – The Bitter Pill: Messaging in Healthcare is Harder
• Why is Healthcare Messaging Harder? 
• Still Worth the Investment

A Quiet Explosion

One interesting thing about staying in a single industry for a long time is that you have the opportunity to watch how knowledge accumulates.  The science around messaging illustrates the point beautifully.  Interest in the formal study of how messaging can be used for persuasion has grown dramatically over the last two decades in academic circles.  One academic synthesis recently suggested a total growth in published experiments on message effectiveness of almost 300% comparing the period from 1985 to 1999 with the period from 2000 to 2010.  In the decade from 2011 to 2020, it more than doubled again.  In practical terms, we now have many hundreds of experimental studies to draw upon to help us make sense of what works and what doesn’t when it comes to communicating with customers.  Notably, this proliferation includes a sharp increase in messaging focus in the domain of healthcare, specifically the increased interest in effective messaging among physicians and health education researchers.  Yet we suspect most marketing and insights practitioners have not had a practical channel through which they could learn about this science.  

This explosion of evidence is a game changer – it presents an opportunity for organizing knowledge in a way that simply was not possible in the past.  To be pointed, it means, we can now begin to:

• Summarize what works and what doesn’t in terms of targeting, frequency and message content.
• Say “how much” of an effect we can expect with one type of messaging strategy relative to another, and how this might differ if we are trying to change attitudes, momentary behavior or durable behavior.  
• Determine how these effects will differ for various types of target outcomes (e.g., changing mindsets versus increasing/decreasing the frequency of behaviors), and different audiences (e.g., socioeconomic and ethnic cohorts).  

We feel pretty sure that we aren’t the only ones who would like to understand these things in advance of developing a campaign.  

In a series of posts, we are going to make the case that a more coherent science of messaging is now available for use by marketers and insights professionals.  This science will allow us to make evidence-based decisions and rely less on popular but largely untested theoretical models.  To keep this fun, we are going to focus on sharing evidence for specific practical insights rather than trying to do a textbook-style integration of the science, but readers with an interest in a more integrated view can reach out to us to set up a discussion.  Here is our first installment.

Lesson 1 – The Bitter Pill:  Messaging in Healthcare is Harder

A 2022 meta-analysis examining messaging effects on various outcome variables found that the downstream effectiveness of healthcare messages is about half that of the effectiveness of messaging in the world of consumer behavior change.  The table below shows these effects starkly.  In the table, K is the number of experimental manipulations included in the analysis and r_ES is the measure of effect size.  The authors compare downstream impact of messaging on attitudes, intended behaviors and actual behaviors in three domains:  healthcare, pro-social activities (such as recycling and energy consumption) and consumer purchasing.  The numbers in parentheses quantify the relative increase in average message effectiveness for pro-social and consumer domains in comparison to healthcare.  We’ll say more about other things we can learn from this analysis in another post, but for now the main point is that the healthcare messages have appreciably less downstream impact compared with similar message structures used in the other domains. 

Table 1:  2022 Meta-Analysis Examining Messaging Effects on Various Outcomes

Another meta-analysis published in 2007, looked exclusively at healthcare behavior change (that is, they excluded attitudes, beliefs and intentions).  Though smaller in scope, the earlier analysis found a mean effect size of 0.074, which suggests that the more rigorous endpoint of observable complex behavior change yields smaller message effects.  In both analyses healthcare effects are extremely modest – certainly “very small” by convention.  It is not unreasonable to use the heuristic that healthcare messages are about half as effective as messages constructed for other domains. 

Why is Healthcare Messaging Harder?

We suspect that these results confirm the assumptions of most life science marketers.  After all, the psychological dynamics associated with healthcare are more complex than most other domains of life.  Without going into endless detail on this point, here are a few illustrative points.    

• Information Avoidance is Inherent in Healthcare
  • In most cases, anything pertaining to healthcare suffers from built in loss-framing because medical conditions typically involve a deterioration relative to one’s current state of health, feelings of well-being, mobility, or functionality.  As the psychologist George Loewenstein explained, this leads to a very natural tilt toward information avoidance.  People would just rather not know.  
• Health-Related Behavior Change Has a Higher “Cost”
  • Most of the time, health behavior change is harder than behavior change in other areas.  Of course, there are exceptions, but most health behavior that we would regard as productive or positive involves (a) getting people to do things they would rather not do that (b) need to be done repeatedly over time (c) without end.  Examples include preparing/eating healthy food, exercise, routine screening and therapy adherence.  
• Intensified by the “Pay Now, Benefit Later” Effect
  • The two points above are made worse by what behavioral psychologists call temporal asymmetry.  With rare exceptions where medical interventions produce immediate (or nearly so) relief from symptoms, the effort you have to expend to engage in health-productive behavior happens now, while the benefits happen later.  Often much, much later.  These effects of temporal asymmetry are NOT to be ignored, as they are some of the most robust, replicable findings in psychological science.
• There is No Guarantee the Effort Will Actually Pay Off
  • To this, we can add the problem of what I would call “probabilistic asymmetry.”  What this means is that, for many conditions, the effort and expense that the patient incurs in addressing the problem is a guarantee.  If you exercise, you will endure the discomfort and time commitment of the activity, for example.  However, the downstream benefits (e.g., reduced risk of heart failure, reduced risk of osteoporosis, reduced risk of falls) are probabilistic.  You may or may not enjoy them.  To make this worse, many health “benefits” that we are trying to communicate are pure abstractions in the lives of busy humans.  In contrast, the money I spend on a prescription, or the time I spend looking for parking at a hospital are very real and palpable.  This phenomenon was first described by health psychologist Gretchen Chapman.  
• The Shrinking Signal-to-Noise Ratio
  • And of course, there’s the signal-to-noise problem.  Humans have become adept at ignoring ads and messages that are not relevant to them, or that they would simply rather not be exposed to.  

Still Worth the Investment

The point of this is that there are good reasons why messaging is harder in healthcare, and the finding is generally sobering.   However, before we lose heart, it is worth remembering that most of these effects are based on a single exposure to a detailed message.  From that standpoint, perhaps these results are actually pretty good.  To make this more relatable, we can transform these meta-analytic findings into a different kind of endpoint.  Rather than use a statistical term, let’s use metric that we like to think of this as the “bodies moved” index – meaning, how many people did I persuade to act or think differently because of my message.  This re-framing of the two meta-analyses gives us a more positive view of the data.

Table 2.  % of People who Think or Behave the Way We Want Them to…

By academic standards, these effects may be small, but viewed in light of “bodies moved” they seem perfectly valuable from a business standpoint.  Further, as we will show in subsequent posts in this series, there are lots of things that we can be doing to improve our healthcare messaging effectiveness.  The main pain is to understand that healthcare messaging effectiveness is something of an uphill battle compared to other types of marketing.  In subsequent discussions, we will show how to use these types of findings to think more strategically about designing messages, channel investment and overall ROI planning for investments in customer communication. 

To learn more, contact us at info@euplexus.com.

About euPlexus  

We are a team of life science insights veterans dedicated to amplifying life science marketing through evidence-based tools.  One of our core values is to bring integrated, up-to-date perspectives on marketing-relevant science to our clients and the broader industry.