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Line 43: − − ==== Contribute to medical research ==== − Variety of literature shows the validity of N-of-1 approaches. For examples search google scholar for patient-led studies.<ref>https://scholar.google.com/scholar?hl=en&q=patient-led+study</ref> 12 self experimenters won Nobel prizes.<ref>https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3298919/</ref> − − Observational studies are important.<ref>https://en.wikipedia.org/wiki/Lead%E2%80%93crime_hypothesis</ref> Epidemiological studies are much easier to conduct with digital tools.<ref>https://www.jmir.org/2022/6/e35804</ref><ref>https://www.researchgate.net/publication/49775085_Reducing_case_ascertainment_costs_in_US_population_studies_of_Alzheimer's_disease_dementia_and_cognitive_impairment_-_Part_2</ref> If continuous self tracking data is taken from multiple people it becomes a longitudinal study.<ref>https://en.wikipedia.org/wiki/Longitudinal_study</ref> These are more reliable than single slice observational studies like the ones most often used by papers about diets. Unfortunately, mobile health companies that aggregate data from users rarely do it with real scientific goals in mind. Instead you should contribute that data to researchers through [[Open Humans]]. Line 56:
Line 56: − + − Most consumers already give lots of data to companies, such as their location via GPS, social media, and their search and browsing history.<ref>https://en.wikipedia.org/wiki/Big_data_ethics</ref><ref>https://www.youtube.com/watch?v=w0NEEmQDVLI</ref><ref>https://www.youtube.com/watch?v=fCUTX1jurJ4</ref><ref>https://www.economist.com/the-world-if/2018/07/07/data-workers-of-the-world-unite</ref> Employers already monitor employee health to optimize the performance of their employees.<ref>https://publications.tno.nl/publication/34623617/ApIQVD/TNO-2015-R11632.pdf</ref> It is possible to do basic cognitive and psychological assessment via background things like speed of typing and semantic analysis.<ref>https://pubmed.ncbi.nlm.nih.gov/19963743/</ref> Also conversations can be summarized with deep learning and emotions detected<ref>https://en.wikipedia.org/wiki/Emotion_recognition</ref><ref>https://en.wikipedia.org/wiki/Emotion_recognition</ref> via cameras.<ref>https://ieeexplore.ieee.org/document/8734245</ref> Companies regularly hoard customer data,<ref>https://old.reddit.com/r/dataisbeautiful/comments/wkzqxs/oc_the_business_apps_that_collect_most_data/</ref><ref>https://www.fiercehealthcare.com/health-tech/report-third-top-hospitals-websites-collecting-patient-data-facebook</ref> sell it to 3rd party aggregators, and get hacked.<ref>https://zerforschung-org.translate.goog/posts/datenabfluss-auf-rezept/?_x_tr_sl=de&_x_tr_tl=en&_x_tr_hl=en&_x_tr_pto=sc</ref> + − Never the less, self trackers can make more data available.<ref>https://www.mobihealthnews.com/news/most-health-apps-have-ability-collect-and-share-patient-data-study-finds</ref> In particular, many devices measure stress and [[Mood]] through [[Tools for heart rate or pulse|heart rate]] and [[Galvanic skin response]], kind of like a polygraph.<ref>https://en.wikipedia.org/wiki/Polygraph</ref><ref>https://www.wareable.com/wearable-tech/wearables-that-track-emotion-7278</ref><ref>https://www.heartmath.com/tech/</ref> + − − Such data has ended up in the hands of employers to squeeze the most out of their employees, as well as mortgage lenders, and insurers to adjust rates.<ref>https://www.tandfonline.com/doi/full/10.1080/03085147.2019.1570707</ref> It was even used to support discrimination and as evidence in court.<ref>https://www.forbes.com/sites/thomasbrewster/2018/01/29/strava-fitness-data-location-privacy-scare/</ref><ref>https://mashable.com/article/period-apps-roe-v-wade</ref> − − Self tracker has some options for defense. Data protection regulations grow.<ref>https://en.wikipedia.org/wiki/General_Data_Protection_Regulation</ref> Government classified [[Commercial, Medical Device, or Open Source|Medical Devices]] make medical data and that data is under more protection than basic commercial device data. Data can be anonymized, though often its not hard to deanonymize it. User should choose companies with terms of service that require opting into user tracking programs. [[Commercial, Medical Device, or Open Source|Open source]] apps, and some commercial ones, are under your complete control and will not mind if the device it runs on never connects to the internet. This wiki will note open source tools and tools with exceptional demand or lack there of for user data. − − ==== Finding and setting up data sources takes time. ==== − User could follow someone else's made trail, such as reading this wiki, instead of researching everything themselves. Uncommon problems, and the exploration inherent in science, require custom data sources that have not been documented here. Learning enough about health and statistics takes time too. − − Greed motivates many companies to make fake and useless devices and interventions.<ref>https://www.jmir.org/2022/6/e37677</ref> Many of the issues described on this page, data quality (devices often cover up bad signal with guesswork), data oversimplification, data access<ref>https://quantifiedself.com/about/access/</ref>, and price are all constraints which make finding a good enough device harder. [[Commercial, Medical Device, or Open Source|Medical and Open Source]] devices have their own issues. Afterwards the explorer will have to aggregate data ([[Open Humans]]), parse new [[Data format structure variables|data format]] and clean the data. Line 82:
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Reasons for and against self tracking and quantification (edit)
Revision as of 19:42, 26 August 2022
, 19:42, 26 August 2022no edit summary
This page is mainly intended to encourage more tracking. It is based off an argument map.<ref>https://www.kialo.com/everyone-should-health-track---self-quantify-49787</ref> If you are not convinced by argument, please read [[Self Tracking, Types Movements Communities|Self Tracking Movements]] for a show of popularity of the practice or [[List of Interesting Self-Tracking Results|Interesting Results]] for examples of successes.
This page is mainly intended to encourage more tracking. It is based off an argument map.<ref>https://www.kialo.com/everyone-should-health-track---self-quantify-49787</ref> If you are not convinced by argument, please read [[Self Tracking, Types Movements Communities|Self Tracking Movements]] for a show of popularity of the practice or [[List of Interesting Self-Tracking Results|Interesting Results]] for examples of successes. Sub-sections are ordered by similarity not importance.
=== Reasons For ===
=== Reasons For ===
Tools to save your life can also record data. For examples; Apple watch monitors for arrhythmia, medicine trackers for the goal of safety can also help monitor health conditions, and hiking is made much safer with GPS.
Tools to save your life can also record data. For examples; Apple watch monitors for arrhythmia, medicine trackers for the goal of safety can also help monitor health conditions, and hiking is made much safer with GPS.
==== Contribute to medical research ====
Variety of literature shows the validity of N-of-1 approaches. For examples search google scholar for patient-led studies.<ref>https://scholar.google.com/scholar?hl=en&q=patient-led+study</ref> 12 self experimenters won Nobel prizes.<ref>https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3298919/</ref>
Observational studies are important.<ref>https://en.wikipedia.org/wiki/Lead%E2%80%93crime_hypothesis</ref> Epidemiological studies are much easier to conduct with digital tools.<ref>https://www.jmir.org/2022/6/e35804</ref><ref>https://www.researchgate.net/publication/49775085_Reducing_case_ascertainment_costs_in_US_population_studies_of_Alzheimer's_disease_dementia_and_cognitive_impairment_-_Part_2</ref> If continuous self tracking data is taken from multiple people it becomes a longitudinal study.<ref>https://en.wikipedia.org/wiki/Longitudinal_study</ref> These are more reliable than single slice observational studies like the ones most often used by papers about diets. Unfortunately, mobile health companies that aggregate data from users rarely do it with real scientific goals in mind. Instead you should contribute that data to researchers through [[Open Humans]].
==== Improve [[Fitness]], [[Mood]], [[Productivity]], and [[Cognition|Cognitive]] abilities ====
==== Improve [[Fitness]], [[Mood]], [[Productivity]], and [[Cognition|Cognitive]] abilities ====
==== For Fun ====
==== For Fun ====
Enjoy playing with cool tech gadgets. Learn a new skill. Satisfy curiosity by looking at the data. Make art out of it and post to r/DataIsBeautiful. Make serious art out of it to bring attention to an issue.
Enjoy playing with cool tech gadgets. Learn a new skill. Satisfy curiosity by looking at the data. Make art out of it and post to r/DataIsBeautiful. Make serious art out of it to bring attention to an issue.
== Reasons Against and Problems ==
== Reasons Against and Problems ==
If appropriate effort is not put in, variables will end up with too much noise and any statistical tests will require too much data. [[Self assessment]] is vulnerable to mood, bias, and ratings drift so it requires extra thought and attention. Users may forget to fill out entries.
If appropriate effort is not put in, variables will end up with too much noise and any statistical tests will require too much data. [[Self assessment]] is vulnerable to mood, bias, and ratings drift so it requires extra thought and attention. Users may forget to fill out entries.
==== Health tracking presents privacy concerns ====
==== Finding and setting up data sources takes time. ====
User could follow someone else's made trail, such as reading this wiki, instead of researching everything themselves. Uncommon problems, and the exploration inherent in science, require custom data sources that have not been documented here. Learning enough about health and statistics takes time too.
Greed motivates many companies to make fake and useless devices and interventions.<ref>https://www.jmir.org/2022/6/e37677</ref> Many of the issues described on this page, data quality (devices often cover up bad signal with guesswork), data oversimplification, data access<ref>https://quantifiedself.com/about/access/</ref>, and price are all constraints which make finding a good enough device harder. [[Commercial, Medical Device, or Open Source|Medical and Open Source]] devices have their own issues. Afterwards the explorer will have to aggregate data ([[Open Humans]]), parse new [[Data format structure variables|data format]] and clean the data.
==== Recording is not necessary to find relationships ====
==== Recording is not necessary to find relationships ====
Why take the time to write things down when user could notice relationships just by paying attention? Its quicker, easier, and far fewer of the reasons not to self track would apply. However, many of the reasons for self tracking can not be satisfied without recording data and most of the relationships will not be noticed as well. Most relationships user would want to uncover require statistical analysis, especially strong effects that can only be seen across long periods. Though, more important effects are usually more sever and easier to notice. Many things a user would want to track require a device and can therefor be automatically tracked with very little effort on the user's part. Noticing relationships relies completely on [[Self assessment]] with all its issues and minus a few of the mitigating techniques. This alternative to self tracking is easier though rarely usable.
Why take the time to write things down when user could notice relationships just by paying attention? Its quicker, easier, and far fewer of the reasons not to self track would apply. However, many of the reasons for self tracking can not be satisfied without recording data and most of the relationships will not be noticed as well. Most relationships user would want to uncover require statistical analysis, especially strong effects that can only be seen across long periods. Though, more important effects are usually more sever and easier to notice. Many things a user would want to track require a device and can therefor be automatically tracked with very little effort on the user's part. Noticing relationships relies completely on [[Self assessment]] with all its issues and minus a few of the mitigating techniques. This alternative to self tracking is easier though rarely usable.
==== User could arrive at wrong conclusions ====
==== User could arrive at wrong conclusions ====
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.
==== Unhealthy engagement ====
==== Unhealthy engagement ====
See also [[Psychological effects of tracking]]. <ref>https://dl.acm.org/doi/10.1145/3274309</ref>
See also [[Psychological effects of tracking]]. <ref>https://dl.acm.org/doi/10.1145/3274309</ref>
Self tracking can feel like a tyrant; demanding and planning things for the user.<ref>https://www.sciencedaily.com/releases/2016/09/160908141724.htm</ref>
Self tracking can feel like a tyrant; demanding and planning things for the user.<ref>https://www.sciencedaily.com/releases/2016/09/160908141724.htm</ref>
Self tracking tools tells user what their goals should be and that can be irritating. Many do not personalize those goals, eg recommending loosing weight to pregnant people. Some push their own agenda, eg lastfm encouraging listening to more music. Apps can produce more psychological pressure to conform to perceived normal. Apps can contribute to legitimized bad ideals.
Self tracking tools tells user what their goals should be and that can be irritating. Many do not personalize those goals, eg recommending loosing weight to pregnant people. Some push their own agenda, eg lastfm encouraging listening to more music. Apps can produce more psychological pressure to conform to perceived normal. Apps can contribute to legitimized bad ideals.
==== Health tracking presents privacy concerns ====
Most consumers already give lots of data to companies, such as their location via GPS, social media, and their search and browsing history.<ref>https://en.wikipedia.org/wiki/Big_data_ethics</ref><ref>https://www.youtube.com/watch?v=w0NEEmQDVLI</ref><ref>https://www.youtube.com/watch?v=fCUTX1jurJ4</ref><ref>https://www.economist.com/the-world-if/2018/07/07/data-workers-of-the-world-unite</ref> Employers already monitor employee health to optimize the performance of their employees.<ref>https://publications.tno.nl/publication/34623617/ApIQVD/TNO-2015-R11632.pdf</ref> It is possible to do basic cognitive and psychological assessment via background things like speed of typing and semantic analysis.<ref>https://pubmed.ncbi.nlm.nih.gov/19963743/</ref> Also conversations can be summarized with deep learning and emotions detected<ref>https://en.wikipedia.org/wiki/Emotion_recognition</ref><ref>https://en.wikipedia.org/wiki/Emotion_recognition</ref> via cameras.<ref>https://ieeexplore.ieee.org/document/8734245</ref> Companies regularly hoard customer data,<ref>https://old.reddit.com/r/dataisbeautiful/comments/wkzqxs/oc_the_business_apps_that_collect_most_data/</ref><ref>https://www.fiercehealthcare.com/health-tech/report-third-top-hospitals-websites-collecting-patient-data-facebook</ref> sell it to 3rd party aggregators, and get hacked.<ref>https://zerforschung-org.translate.goog/posts/datenabfluss-auf-rezept/?_x_tr_sl=de&_x_tr_tl=en&_x_tr_hl=en&_x_tr_pto=sc</ref>
Never the less, self trackers can make more data available.<ref>https://www.mobihealthnews.com/news/most-health-apps-have-ability-collect-and-share-patient-data-study-finds</ref> In particular, many devices measure stress and [[Mood]] through [[Tools for heart rate or pulse|heart rate]] and [[Galvanic skin response]], kind of like a polygraph.<ref>https://en.wikipedia.org/wiki/Polygraph</ref><ref>https://www.wareable.com/wearable-tech/wearables-that-track-emotion-7278</ref><ref>https://www.heartmath.com/tech/</ref>
Such data has ended up in the hands of employers to squeeze the most out of their employees, as well as mortgage lenders, and insurers to adjust rates.<ref>https://www.tandfonline.com/doi/full/10.1080/03085147.2019.1570707</ref> It was even used to support discrimination and as evidence in court.<ref>https://www.forbes.com/sites/thomasbrewster/2018/01/29/strava-fitness-data-location-privacy-scare/</ref><ref>https://mashable.com/article/period-apps-roe-v-wade</ref>
Self tracker has some options for defense. Data protection regulations grow.<ref>https://en.wikipedia.org/wiki/General_Data_Protection_Regulation</ref> Government classified [[Commercial, Medical Device, or Open Source|Medical Devices]] make medical data and that data is under more protection than basic commercial device data. Data can be anonymized, though often its not hard to deanonymize it. User should choose companies with terms of service that require opting into user tracking programs. [[Commercial, Medical Device, or Open Source|Open source]] apps, and some commercial ones, are under your complete control and will not mind if the device it runs on never connects to the internet. This wiki will note open source tools and tools with exceptional demand or lack there of for user data.
== References ==
== References ==