In part 1, we introduced many reasons why something might seem to work (like an exercise program, a sort of therapy, a nutritional supplement, etc.), when in fact, it doesn’t!
It was a good starting point, as it helps to understand how we can be wrong when we make important health decisions based on intuition rather than evidence. If you haven’t read it yet, check it out. It sets the stage for understanding why science is so important.
But before we get too deep into the discussion of why science is important, we should first understand what it is, and what it’s not.
NOTE: Keep in mind that this discussion will center around science and how it relates to health (since that’s what this site is generally about) – therefore, these definitions may not encompass all the nuances of every field of science (e.g. political science, physics, etc.). Also, note that this is a working definition for our purposes – if you really want to talk about what science is and isn’t, I suggest you read one of the many books written on the philosophy of science!
- Science (from the Latin word ‘scientia’, meaning ‘knowledge’) refers to the body of reliable knowledge about a topic, as well as the process of attaining and organizing that knowledge (the scientific method).
Reliable is an important word here. Science refers to knowledge that can be logically and rationally explained (it has to make sense, and stand up to harsh criticism). Furthermore, in order for this knowledge to be used in making reliable predictions (like whether a drug will work in a particular patient or not), it has to be testable (you should be able to prove it through repeatable observation and rigorous experimentation).
THE SCIENTIFIC METHOD
The scientific method is the process of testing an observable occurrence, gathering new information, and integrating this new information into previously existing knowledge.
It goes like this (with an easy example):
- Question: you notice something in the world that makes you curious, and you want to know more about it. For example, you’re a researcher, and you just read a study showing that a particular exercise program caused a group of athletes to run faster. So you develop a question, like “Why did this exercise program improve running speed in that group of athletes?”.
- Hypothesis: before proceeding with an experiment, you must first try to logically explain what you’ve observed based on previously existing knowledge. That proposed explanation is called a hypothesis. With this hypothesis, you can make testable predictions. For example: you may hypothesize that “This exercise program strengthens those athletes leg muscles, which in turn allows them to run faster”.
- Prediction: Then, you make predictions that are testable. For example, based on that hypothesis, there are at least two predictions you can make: 1. “this exercise program makes the leg muscles of these athletes stronger.” 2. and “stronger leg muscles make these athletes run faster.”
- Experiment: The next step involves putting your ideas to the test – literally: you design an experiment that measures the things you are interested in. For example, you gather a group of athletes, measure their leg strength and run speed, make them complete the exercise program for 10 weeks, and then measure their speed and strength again. Once you’ve collected the data, it’s time to move on to the next step. Your data is only as good as your experimental design.
- Analysis: Once the experiment has been completed, you collect the data and begin the analysis (you figure out what the results actually mean). Usually, you would do some statistics on the data (which can be very simple, like making charts and graphs, or very complex, using complicated computer programs). Once the data is analyzed, you can start to interpret your results.
For example: maybe the data in our imaginary experiment demonstrated that the exercise program succeeded in making leg stronger on average. However, the athletes who made the biggest gains in leg strength were not the athletes who made the biggest gains in speed – i.e. strength and speed were not correlated. Therefore, it must be something else about the exercise program that caused improved running speed, not leg strength.
- Repeat: Even though we’ve learned a few important facts from that experiment, we still have many questions left to answer. This is usually how science goes!
People often refer to “science” and “the scientific method” as the same thing, which illustrates just how important the method is. It’s this method that makes the knowledge reliable. However, “science” can also refer to what knowledge has already been established through the scientific method, or what we can reasonably deduce or induce from previous observations and experiments.
Always keep the importance of the scientific method in mind – if the above steps were not used to gather the information, it’s difficult to call that information “scientific”. There are exceptions, but we have to be careful with them!
Having a basic understanding of the process, you should now see that merely sounding like science (i.e. ‘pseudoscience’) doesn’t actually make something ‘scientific’.
For example, countless exercise programs, nutritional supplements, and therapies may be based on science, but they remain in the hypothesis phase. No actual testing has been done to see if it works, or how. Therefore, even if the claims made by proponents or marketers are true (who knows? maybe it does work), it’s still not “scientifically proven”. In fact, very few things actually are.
Of course, it’s okay to do things that make sense – sometimes we just don’t have good science to rely on. Sometimes, we don’t even need it. But when science is available, and it’s good science, then we should probably pay attention to it!
Now that you understand a little better what science is, it should be clear that science doesn’t “know” everything, and probably never will. For example, it’s pretty hard to imagine an experiment that can prove or disprove the existence of ghosts, or to figure out whether your girlfriend will marry you or not. But for many questions, it’s the best method we have for determining the truth, free from our biases and beliefs.
Science is not an institution or authority that’s out to control what we all think. If that ever appears to be the case, it’s not science that is at fault. Usually, it’s those who are in control of what science is performed and presented – those providing the funds, or scientists with a shady agenda.
Science is a body of reliable knowledge and a method we can all use to investigate things where our intuition would otherwise be unreliable. Sometimes our intuition is enough – we don’t need an experiment to determine whether I can jump 10 feet into the air, or that stabbing monkeys causes them to die. But for more complicated things – like how an exercise program works, or a drug, or a therapy, or any of the other infinite questions we have about our health, it’s not just helpful – it’s often necessary.
When making decisions that have important consequences on the health and well-being of our societies, we need a tool that’s reliable. So far, science is the best tool we have.