Interpretation of data is something what I am doing a lot. When I am looking at my Fitbit sleepdata, happiness-data, steps during the during the day, or HRV in the morning I interpret my data. When I see a sleepscore of 45% in my Fitbit app, does that mean I had a bad night? I my HRV is 30, does that mean I have stress?”, If I stepped 3.000 steps today, am I inactive? These interpretations are crucial during behavior change. How do you interpret you data? Viewing, interpreting, and using your data could potentially change your life, thus it is every important you interpret it wisely. Your life kinda depends on it. Basically, there are two different ways to interpret your personal data. Which are very important distinctions. The first one is the data-conformist. The second one is the other way around, which is the data-protester.
In this case, you take data as a truth-teller, you conform with the data that is collected. The data you collect says everything about your life. The steps you track define your physical activity, the HRV you track defines your stresslevel, and the sleep you track defines your sleep quality. Using your data like this can be very useful and very insightful to you. If you take your data as the truth, it is very easy to change your life based on your data.
However, some of you might have a problem with the first view. In this case, where you refuse the outcomes of your data, you don’t take data as the truth. But you interpret your data how it seems fitting to you. Your step tracker might say something about your physical activity, but doesn’t say everything. You might argue that some of your tracker is inaccurate or that your tracker doesn’t measure your swimming activities. Thus, you will continue living and take your data with a little grain of salt. In this case, the chances are lower that you will change your life based on your data.
What is the best way?
Of course, as with every cheesy blog article, there is no best way. The more you come the point where the data defines you, the more useful it becomes. However, today (2017) trackers don’t measure everything that is important, and are often inaccurate. Thus, you should ‘t use trackers as a truth-tellers. However, if you interpret your data just as you please, you might have chosen the wrong path as well. In this case, the data might have shown you the truth, but if you choose to ignore that, you will never change your behavior.
There is some rationality, and knowledge needed to choose the most effective path. It really depends on the things you are tracking (and how), and on the things you want achieve. The validity, accuracy, ans reliability of the measurements are very important when interpreting your data. But you have to remember that most measures don’t tell you total bullshit. If you walk 13.000 steps, a step-tracker might be a few 100 steps off, but the measure will be around the 13.000 steps somewhere. Sometimes it is not really about the exact value, but it is about the trend in your data.
You should also be aware of your own personality. Scientific studies have shown that “winners” tend to blame others when things go wrong (external attribution). This is the same risk with trackers, if you are a “winner”, but your tracker shows bad outcomes you have higher chances to blame the tracker and say it is inaccurate. On the other side, “losers” tend to blame wrong outcomes on themselves when things go wrong (internal attribution). When their tracker has bad outcomes, they will blame themselves. When things go well, they will say that the help of others made them win (externally attribution). What kind of person are you?
Your first response to your data outcomes tells often a lot about yourself. Are you more likely to deny or to conform with outcomes/statements/arguments? Try to figure out what your instinctive responses are when something evokes a reaction. This might be very helpful to you to see what kind of person you are. You can also test this when having an argument with someone; what is your first response; conforming or denying?
A few tips to make your tracking useful:
– Check what kind of person you usually are; conformist or protester
– Look at your first responses
– Check deep inside whether you are lying to yourself
– Look into the science behind your tracker
– Use rationality when looking at your data
– Track more things to increase accuracy
– Measure subjective experiences, which are the truth to you (but might not be reality)