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Reasons for and against self tracking and quantification (edit)
Revision as of 01:18, 23 May 2022
, 01:18, 23 May 2022→Reasons Against and Problems
== Reasons Against and Problems ==
== Reasons Against and Problems ==
==== Self tracking takes too much time and effort every day. ====
==== 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. Effort is hard to define as some people like Journaling and others do not.
Manual entry is time consuming though automatic data recording is usually not. Studies and experience show people dropping even fitness tracking smart watches. Effort is hard to define as some people like Journaling and others do not.
* Almost none: [[Tools for heart rate or pulse|Smart Watches and Rings]] , [[Time tracking|Automatic Time tracking]], already tracked personal data like [[Social media]] or your Calendar , public info like [[Weather|Outdoor Weather]],
* Almost none: [[Tools for heart rate or pulse|Smart Watches and Rings]] , [[Time tracking|Automatic Time tracking]], already tracked personal data like [[Social media]] or your Calendar , public info like [[Weather|Outdoor Weather]],
* A few minutes each day: [[Weight tracking|Weight scale]], [[Tools for heart rate or pulse|Exercise Heart Rate Strap]], [[Tools to survey symptoms and states|Rating Mood]] at end of each day.
* A few minutes each day: [[Weight tracking|Weight scale]], [[Tools for heart rate or pulse|Exercise Heart Rate Strap]], [[Tools to survey symptoms and states|Rating Mood]] at end of each day.
* Over 10 minutes each day: [[Tools for Cognitive Testing|Cognitive Tests]], [[Diet tracking]], manual [[Time tracking]], [[Tools for journaling, thoughts and note taking|Journaling]]
* Over 10 minutes each day: [[Tools for Cognitive Testing|Cognitive Tests]], [[Diet tracking]], manual [[Time tracking]], [[Tools for journaling, thoughts and note taking|Journaling]]
==== People make mistakes forget and slack when recording data manually ====
==== Health tracking presents privacy concerns ====
Self-report is a common concern in studies.
Most consumers already give lots of data to companies, such as their location via GPS, social media, and their search and browsing history. Employees already monitor employee health to optimize the performance of their employees. It is possible to do basic cognitive and psychological assessment via background things like speed of typing, semantic analysis and emotion detection<ref>https://en.wikipedia.org/wiki/Emotion_recognition</ref> via cameras. Never the less self trackers can make much more data available.
Self tracking user has some options for defense. Data protection regulations grow.[https://en.wikipedia.org/wiki/General_Data_Protection_Regulation] [[Commercial, Medical Device, or Open Source|Open source]] apps are under your complete control and will not mind if the device its on never connects to the internet. Government classified [[Commercial, Medical Device, or Open Source|Medical Devices]] make medical data and that data is under far more protection than basic commercial device data. This wiki will note open source tools and tools with exceptional demand or lack there of for user data.
==== Health tracking presents privacy concerns ====
==== Choosing, setting up, and connecting user's selection of apps and devices can be quite a bit of work. Or expensive. ====
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, and price are all constraints which make finding a good enough device harder.
==== Analysis algorithms are either hard to use or too simple ====
==== Analysis algorithms are either hard to use or too incapable. ====
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.
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.
==== Negative engagement of User ====
==== Negative engagement of User ====
such as becoming obsessed with data tracking.
such as becoming obsessed with data tracking.
==== People make mistakes forget and slack when recording data manually ====
Self-report is a common concern in studies.
==== People do not want to know somethings ====
==== People do not want to know somethings ====