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In the context of health-related questions, it might also be better to start from exploring ones own experiences rather than trying to dive into trying to find causes right from the start. Collecting data to conclusively "proof" a certain diagnosis is a very high bar to take and can be an overwhelming task to start out in a personal science project. Instead, it might be worth focusing on questions like "How bad are my symptoms?", "How often do they occur?", "What helps to improve my condition?". Framing questions this way might make it easier to make observations and reason about the records one collects.
In the context of health-related questions, it might also be better to start from exploring ones own experiences rather than trying to dive into trying to find causes right from the start. Collecting data to conclusively "proof" a certain diagnosis is a very high bar to take and can be an overwhelming task to start out in a personal science project. Instead, it might be worth focusing on questions like "How bad are my symptoms?", "How often do they occur?", "What helps to improve my condition?". Framing questions this way might make it easier to make observations and reason about the records one collects.
== Observing ==
Once one has decided on what kind of questions one would like to pursue, it is time to think about how to answer it. Virtually all self-research projects require making deliberate observations. This requires selecting some parameters that one wants to pay special attention to to keep track of them. There are some things to consider when selecting what to observe.
* '''Relevancy''': Does observing this offer insights into what I really care about?
* '''Convenience:''' Can I collect these observations easily and consistently?
* '''Trustworthiness:''' Am I confident in the measurements?
On some level these things are interrelated. For example, using a digital tool such as a wearable device can be a very convenient way to passively collect data such as daily step counts. But is measuring steps really relevant for the question at hand? And how confident can one be in that the step counts are correct? In many cases it might be necessary to decide on trade-offs between these points.
Another good rule of thumb for observations is that the events or phenomena that one plans to record should be '''noticeable''', '''variable''' and '''distinct''' as this will help facilitate recording the observations and reasoning about them later on. Having noticeable events helps recording the data, in particular when doing so manually by entering data by hand into a notebook, spreadsheet or mobile app (e.g. symptom recordings). Variability is important, as events that never change in frequency or intensity or any other dimension will not provide any insights (see relevancy above). Lastly, having distinct events is important to be able to correctly record observations as a lack of distinctiveness makes it hard to "correctly" count how often a thing happens.
=== Using proxies ===
Many things one might want to observe can be either hard to quantify (e.g. the abstract idea of "fitness") or hard to consistently observe because it would be too challenging to collect the "ideal" data over a period time. In such cases one can try to replace the direct observation through a proxy measurement that is closer to the ideal conditions outlined above. For example, instead of measuring "fitness" one could track physiological values such as [[HRV (Heart Rate Variability)|Heart Rate Variability]] or how fast one runs, how many weights lifted etc.
=== How to observe and record ===
== References ==
== References ==
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