The Special Problem of “Unchallenged assumptions”, “Biased thinking” and “Meaningless Averages” in the Aging space

Although this article is undoubtedly something of a rant I firmly believe that we encounter all 3 of the problems described in the title here both individually and, at times, all at the same time. As a result, I want to describe how these problems tend to show up and why we should be extra-vigilant when they do.

Before we consider the impact of these thinking problems collectively, let’s first look briefly at how these problem occur and typically manifest themselves.

Unchallenged assumptions

We all make assumptions in order to live our lives. At the most basic level we assume our parents/grandparents, for example, will continue to wake up in the morning, be able to drive or get around easily, have enough money, avoid falling over, find friends etc. In fact these kinds of assumptions are so automatic or embedded, we rarely give them much thought day to day. However, beyond these general assumptions, we may have more specific beliefs too. This might include that our parents/ grandparents are safe from abuse, are taking their prescribed medications properly, are eating a healthy diet, are remembering to pay bills when due and are making smart decisions most of the time.

These assumptions are all “true” to a greater or lesser extent of some people and for some of the time but we will also equally find these are not true for some people and for some of the time (and of course it is on us to check what is factually true).

For an entrepreneur or startup company this is a crucial issue and we need to look for as many ‘hard’ facts as possible to validate that what we are building or how we are offering to help is going to apply and be useful in real terms.  In other words, it is often an extremely helpful exercise to challenge our assumptions directly or to analyze on what foundation we are basing our thinking. This also helps us to avoiding making unhelpful generalizations about people which mask what might really be happening at a more granular level.

Biased thinking

Biased thinking is mainly caused by deploying mental shortcuts, or heuristics, which are sometimes also called thinking “rules of thumb.”

These biases are not necessarily all bad, because some of them allow us to reach decisions quickly. This can be vital if we are facing a dangerous or threatening situation or simply want to save time-for example, a bias that a spaniel is likely to make a better pet for an older adult than a Doberman is simply a convenient way to make a choice even though many Dobermans may well be great pets for a senior.

Unfortunately many biases can be more invidious and lead to flawed thinking and there are many types to guard again. This includes:

·     Confirmation Bias: where a person favors information that conforms to his or her existing beliefs and discounting evidence that does not conform. For example, people over 70 years old tend to be frail.

·     Attentional Bias: Paying selective attention to some things while simultaneously ignoring others. For example, older adults living in assisted living have plenty of people around them so can’t be lonely.

·     Anchoring Bias: Relying too heavily on the first piece of information you receive as true and then comparing all that comes after it. For example, you may be told Mary is a diabetic but then see everything else you are told about her through this lens.

·     Optimism Bias: A belief that people’s situations will improve over time. For example, Bob’s knee replacement will mean he’ll quickly be as mobile as he was before.

Sadly these 4 are only a few of at least 30 specific thinking biases that psychologists can tangibly identify!

When it comes to thinking about older adults-specifically and generally, these and other biases mean that we are in danger of ignoring facts and evidence and thereby making a wrong judgment or decision. For an entrepreneur or startup company this clearly doesn’t help when we need to carefully and accurately consider what changes may bring benefits but are using broad generalizations and rules of thumb to make our contributions to the debate.

Meaningless Averages

The third and last of these thinking problems is perhaps the hardest to spot and do something about. Meaningless averages are similar to cognitive biases in that they are often generalized “rules of thumb” that people carry around with them through time. Even worse, the “average” is a convenient proxy for what is happening at a much more granular level (and often disguised or made “bland” by the mean).  A fairly innocuous version of this is that “men in the US die at 78 on average and women at 80”. But even this belief is fairly meaningless when we want to address issues around better longevity or better healthcare decisions have to be made. For example, these figures were actually true on average 3 years ago-today they have fallen slightly to 77 and 79 (heavily influenced by rising earlier deaths as a result of obesity and excessive opioid use). In addition, these numbers vary greater by State in the US-a spread of 6 years top to bottom) and by even by city or rural area (and that spread is even worse on a worldwide level by the way where the gap between best to worst is currently around 43 years!). Perhaps even worse, such averages say nothing about quality of life and only focus on quantity-dying quickly without major disease at 80 is very different to dying at the same age with many chronic conditions and suffering. Furthermore it may be that high levels of child mortality, for example, are driving this “average” number to be a lot lower than it should be if this were addressed. This simple average statement then is pretty meaningless. 

Once we get into more “questionable” averages, the problems are even greater. To take a very specific example, we might hear “The cost of Medicare per senior of 65 and over in the US is $15,000”. Such a number is a simple calculation of the total Medicare budget divided by the number of seniors covered. This quickly leads many people to then believes that this cost relates to medical bills and the resultant thinking that seniors are expensive to keep well or even alive. When we dig even a little bit deeper into these numbers (which have the same issue of being very different by State, County and City or rural area by the way) we find that the costs are quite different for men and women, that administrative costs are 40% of the total and that a huge 20% of this cost is accounted for by the top 2% of people covered (to take just 3 examples). This clearly leads at best to “muddled thinking” and at worst to piecemeal decisions and changes that may or may not lead to improvements.

For an entrepreneur or startup company finding good data is critical but the above suggests that we have to be very careful about generalizations and averages that seem to tell an overall story but may not be very representative when you dive deeper.

While all of the above can and do occur individually, in some cases, it may be that all three problems can occur simultaneously. For example, the headline I read recently that said “The US is heading into a dementia epidemic” has an assumption behind it that people know what dementia is (there are 4 different types of which Alzheimer’s is one for example) and it qualifies as an epidemic (which according to the World Health Organization’s definition it does not by the way). This headline may lead us to apply confirmation bias because we have a relative or friend with dementia (and we didn’t have one before!). Finally we may even start to read articles which offer “meaningless average” statements such as “50% of residents in assisted living have dementia” as an all-encompassing fact (when actually the evidence here is both anecdotal and hugely varied across the country, with the level of dementia being experienced highly varied).  

One last example I heard recently from a so-called “expert” on a healthcare panel who said “I assume that the average age of a person in a skilled nursing facility is in his or her early 80’s, female, single and likely to be isolated and lonely-we need to think about this person when delivering better healthcare in the future.” There you have it, without even unpacking the statement, this person has fallen into all 3 traps at the same time in my view.

My overall point in this article is not to suggest that unchallenged assumptions, cognitive bias and meaningless averages are not likely to disappear any time soon, but merely to suggest that we can all invest more time in reflecting on whether we can do more to avoid these “traps”. And just remember, when it comes to improving the lives of our burgeoning older adult population, who are already relatively marginalized in society, this may often become a life or death issue!

Jon Warner is CEO of Silver Moonshots, a research and mentoring organization for enterprises interested in the 50+ older adult markets. He is also Chapter Ambassador for Aging 2.0 in Los Angeles and Co-chair of the SBSS “Aging in the Future” conference, in Los Angeles.