Editing Reasons for and against self tracking and quantification

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Wrong conclusions could be dangerous to user's health. User should of course double check with experts like doctors and veterans of the community (and this wiki). Learning enough about health, experimentation,<ref>https://www.frontiersin.org/articles/10.3389/fdgth.2020.00003/full</ref> and statistics takes time that many do not have.  
 
Wrong conclusions could be dangerous to user's health. User should of course double check with experts like doctors and veterans of the community (and this wiki). Learning enough about health, experimentation,<ref>https://www.frontiersin.org/articles/10.3389/fdgth.2020.00003/full</ref> and statistics takes time that many do not have.  
  
Analysis algorithms are either hard to use or too incapable. For example, article in Nature where ML was used in multiple N-of-1 studies and that approach is both incomplete and difficult for the average user.<ref>https://www.nature.com/articles/s41398-021-01445-0</ref> [[Finding relations between variables in time series|All data aggregators]] for self tracking, besides OH, use linear regression or nothing at all. This problem can sometimes be avoided with [[Experiment VS Observational study|careful experimental design]] like RCT.  
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Analysis algorithms are either hard to use or too incapable. Article in Nature where ML was used in multiple N-of-1 studies but that approach was both incomplete and difficult for the average user.<ref>https://www.nature.com/articles/s41398-021-01445-0</ref> All data aggregators for self tracking, besides OH, use linear regression or nothing at all. This problem can sometimes be avoided with [[Experiment VS Observational study|careful experimental design]] like RCT.  
  
Sources can be misleading. Food companies will give bad data to make themselves look good. Even user can have biases for various reasons listed in "negative engagement of user".  
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Sources can be misleading. Food companies will give bad data to make themselves look good. Even user can have biases due to "negative engagement of user".  
  
 
User's doctor may not be able to help. Use of self tracking is not wide spread through medical community. Except for a few key vitals, doctors do not use the types of data self trackers do. Doctors are not skilled in advanced statistics.
 
User's doctor may not be able to help. Use of self tracking is not wide spread through medical community. Except for a few key vitals, doctors do not use the types of data self trackers do. Doctors are not skilled in advanced statistics.

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