Changes

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.   

Assessments about aggregated intervals can also be presented at random intervals or constantly in small pieces or at user's convenience e.x. before going to bed.     

Assessments of aggregated intervals can also be presented at random intervals or constantly in small pieces or at user's convenience e.x. before going to bed.     

==== Scales ====

==== Scales ====