This document discusses problems with self-reported medical data from users, including regional idiosyncrasies, cognitive biases, and the desire to be unique that can affect accuracy. It suggests that automatic tracking from devices or standardized question formats may help mitigate these issues by reducing biased self-reporting.

1. On your Libido, Eye Colo(u)r and
Broccoli Preferences: Problems
with Self-Reported (Medical) Data
Samantha Clark (@iameltonjohn)
Bastian Greshake (@gedankenstuecke)

2. Our Interest
• Started
• Allows users to share genetic data, along with
(medical) information
• Right now: ~120 different traits/phenotypes

4. Regional Idiosyncrasies

5. Regional Idiosyncrasies

6. Further Problems
The Desire to be Unique

7. The Desire to be Unique

8. The Desire to be Unique

9. Even More Problems
Cognitive Biases

10. Cognitive Biases

11. Cognitive Biases

12. Not all questions are useful

13. Possible Mitigations
Disclaimer: Not all of those have been tested by us

14. Questionnaires

15. Questionnaires

16. Automatic Tracking
http://dl.maclife.com/maclife_photos/0510/reviews/fitbit_full.jpg

17. Automatic Tracking
http://dl.maclife.com/maclife_photos/0510/reviews/fitbit_full.jpg

18. Magic
Histogram: http://www.canon.ca/support_images/KB_Images/G0034801.jpg
Beard: http://i98.photobucket.com/albums/l247/g0machamp/014-7.jpg

19. Magic

20. Conclusions
People don't mind answering questions about themselves,
but they aren't necessarily too good at providing unbiased
answers in a unified metric.
Some things that may help this in the future are standardized
or automatic data collection.