Changes

The whole act of manually trying to turn experience into a number. Not self report because you are not reporting to anyone but yourself and so other people's opinions do not matter. According to the wikipedia, this process is called something else<ref>https://en.wikipedia.org/wiki/Ambulatory_assessment</ref><ref>https://en.wikipedia.org/wiki/Experience_sampling_method</ref>, not self assessment<ref>https://en.wikipedia.org/wiki/Self-assessment</ref>.  

The whole act of manually trying to turn experience into a number. Not self report because you are not reporting to anyone but yourself and so other people's opinions do not matter. According to the wikipedia, this process is called something else<ref>https://en.wikipedia.org/wiki/Ambulatory_assessment</ref><ref>https://en.wikipedia.org/wiki/Experience_sampling_method</ref>, not self assessment<ref>https://en.wikipedia.org/wiki/Self-assessment</ref>.  

User can do the assessment right after an incident or as an aggregate of a recently passed time period. Most things user would want to measure do not occur as easily defined and measured incidents so aggregation will need to be used. Unfortunately, having to remember a state over many hours requires effort and creates ambiguity. In addition, the method of aggregation (mean, mode, extremes) loses information, take a bit of effort, and can be a cause of drift. By information loss I mean that if a weighed mean is used to represent a time series the distribution is lost. For example, pain that spikes to high values for a few minutes every hour can have the same number as just pain that stays the same throughout the time period.   

User can do the assessment right after an incident or as an aggregate of a recently passed time period. Most things user would want to measure do not occur as easily defined and measured incidents so aggregation will need to be used. Unfortunately, having to remember a state over many hours requires effort and creates ambiguity. In addition, the method of aggregation (mean, mode, extremes) loses information, take a bit of effort, and can be a cause of drift. By information loss I mean that if a weighed mean is used to represent a time series the distribution is lost. For example, pain that spikes to high values for a few minutes every hour can have the same number as just pain that stays the same throughout the time period.