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Reasons for and against self tracking and quantification (edit)
Revision as of 06:56, 17 November 2021
, 06:56, 17 November 2021→Reasons Against and Difficulties
User could follow someone else's made trail such as reading this wiki instead of researching everything themselves. Custom data sources such as for rare problems that have not been documented here are still a problem. Privacy, data access, data quality are all constraints which make finding a good enough device harder.
User could follow someone else's made trail such as reading this wiki instead of researching everything themselves. Custom data sources such as for rare problems that have not been documented here are still a problem. Privacy, data access, data quality are all constraints which make finding a good enough device harder.
==== Self tracking takes too much time and effort every day. ====
Manual entry is time consuming though automatic data recording is usually not. Studies and experience show people dropping even fitness trackers.
==== People make mistakes forget and slack when recording data manually ====
==== People make mistakes forget and slack when recording data manually ====
Self-report is a common concern in studies.
Self-report is a common concern in studies.
GPS can reveal delicate information. Same with emotion detection. Employees already monitor employee health. User has some options for defense. Data protection regulations grow.
GPS can reveal delicate information. Same with emotion detection. Employees already monitor employee health. User has some options for defense. Data protection regulations grow.
==== Self tracking takes too much time and effort every day. ====
==== Analysis algorithms are either hard to use or too simple ====
All apps besides OH with any ability to analyze just use linear regression. Just read an article in nature where ML was used on multiple N-of-1 studies but that approach was lacking and is difficult for the average user to set up.