Self-Tracking Basics: Operationalization

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quantified self self quantification self tracking self experimentation personal analytics basics by measured me blogOne of the major challenges you face before you even start self-tracking is defining in plain terms how to measure the variables of interest. In experimental social sciences, there is a special term for that: operationalization. It refers to defining the variable of interest via empirical (measurable) qualities. In other words, you define it in terms of specific operations by which you will be measuring it, and then stick to that operational routine. For instance, you would like to track quality of sleep. Now, you can measure it in many different ways.

You can ask yourself upon awakening to rate your sleep on a five-point scale, from “not good at all” to “excellent”. You can also count how many times you woke up during the night. Or you can record how much time does it take for you to get out of bed after you woke up. If you prefer more objective measures, you may choose to rely instead on devices like mobile phone (Sleep Cycles or Smart Alarm clock apps) or more advanced device (BodyMedia, Zeo, FitBit) to collect certain sleep statistics (e.g., length of REM sleep).

My word of advice: instead of relying on intuition and personal understanding of subject, turn to professionals and academics, and conduct some diligent research (e.g., using Google Scholar) before you start logging data. Trust me, no matter what you are trying to measure, the chances are that someone out there has already done some empirical research on the subject. Relying on solid scientific research is especially important if you are trying to measure a psychological trait or other intangible construct. You want to have a valid and reliable questions to measure the variable of interest, questions that have been successfully tested already on many people. Otherwise you risk to end up with messy, unreliable data that won’t provide you with any meaningful insights.

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