Truth In Cycling

Over and over again, I hear snake oil claims in the cycling world.

I argue against them because I love to do so, but I figured that I should put my own standards for what is and is not true down in one place. This is not an exhaustive article, but it’s a starting point on what I think to be “true”.

First of all, I like studies. Just having you stuff in a pdf which is formatted like a scientific paper with charts and graphs makes me feel like I’m reading “data” instead of opinion. This is a bias of mine. I don’t think that biases are necessarily bad. I like to put my own biases out there; I like to be honest about these things. I expect the same level of honesty from others.

Back to studies: a good study is one in which it has a specific question which it asks. For example, for Vehicular Cycling: “Those who take cycling safety classes and practice its techniques consistently are less likely to sustain a serious injury or death in an collision with an automobile. This study will measure how much safer they are.” Then at the end of the study, we find out how much safer people are. We have a number that we can try to reproduce in other circumstances.

These studies are not hard to do. Relative to the amount of money we spend on classes and helmets and PSAs, these studies are highly inexpensive.

Another thing makes a study good is when one defines one’s terms ahead of time and gives good cut offs. For example, we hear that cycling is safe or unsafe or whatever. For me, the question is what does safe mean? Everyone uses this word, but few define it. I have looked for a definition and I accept WHO’s because it’s the only large organization which made such a study easy to find on the internet. Next time someone tells you something is safe or unsafe ask them how many people per 100,000 have to die or be seriously injured before you’d change your mind in what is or is not safe. If they don’t know then you are talking to someone who is merely speculating or they are blathering about their feelings. I like feelings and talking about them, but let’s not put our personal feelings out there like they are the truth.

Note, that we need to do all of this _before_ we gather data. There’s something about the human mind called confirmation bias which makes us look for data whihc confirms our position, only, once we are locked in. That’s why we need to get the standards created ahead of time. Otherwise, we’ll be tempted to move the goal post.

So when we safe helmets are “safer” what does that mean?

What’s a “helmet”? If we are going to compare helmets vs. non-helmets, we need to standardize our subjects on a particular make and model of helmet and talk about that. This is how real science works. In chemistry, we not only tell what chemicals we use, but we try to tell the manufacturer, too. This is because there are sometimes impurities in compounds which affect a reaction. Different impurities can have different effects. Different manufacturers can have different impurities. So if an experiment fails, it’s nice to look at who made our compounds and what the impurities are.

In pro-helmet studies, they never look at the differing manufacturers. This is because there are a bewildering array of different manufacturers with different helmets. This is like having a study which says that “vitamins are good for you” but we never look at which specific vitamins taken by which specific population and which specific doses. We just measure people who pop random pills vs. those who don’t. We don’t even give a defition of what “healthier” is. We do have a lot of graphs and numbers though based on circumstantial evidence. This study would be considered garbage in the medical world, but it’s the level of standard for our helmet studies where we measure children falling off their bicycles then we take that data and try to apply it to adults getting hit by high speed cars.

We’re not done! Next we need to look for confounding factors. For example, people who wear helmets are probably safer riders. We don’t know for sure, but they might be. One way to eliminate this confounding data is to pay people who normally would NOT wear helmets to wear them. Then we pay people who would wear them to not wear them.

Next we need to get a good statistician to make up the standards, as per above, on what is and is not acceptable. For example, if we see that there are 50% less visits to the ER by people who wear our standard helmet regardless of whether they were in our “safer riderss” category, we have a valuable claim. Otherwise, we don’t say that helmets are safer. I’m using 50% as an example. I don’t know how much safer helmets need to be because I’m not an expert in safety. I do know that no paper on helmets that I have read is up front on defining “safer standards.”

No safety equipment is safe 100% of the time. But we need to be safer than not in order to have a valid claim.

Finally, we conduct our experiment. We buy helmets from the same manufacturer and give them to cyclists to wear starting on the same date. Or we give cycling safety classes to those who normally would not take them. All of our cyclists wear wrist bands which tell the ER which data to collect and who to call with it.


Until we see some good studies, using concepts as per above, let’s stop making outlandish safety claims. At best, we say that these things are unknown in their benefits. But for some reason when people see “unknown” they latch on to stupid nonsense like “better safe than sorry.”

No, we are better safe when we take an honest and sober approach to safety not when we waste money on questionable safety schemes. There are things which do make cyclists safer. They have been proven. Let’s spend all our money on those. Every last cent should go to things that we know that work.

Once we have reached diminishing returns which will be billions of dollars later, we can look into more marginal safety devices such as helmets and classes. But we need to be wise with our money. Otherwise, we’ll continue to get the same piss poor safety ratings we have had for the past few decades and our mode share will remain at a stangnant 1% which is where it should be based on the stupid and unproven notions which have been used to promote cycling safety.


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