Scaling Self-Experimentation
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Scaling Self-Experimentation

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Presented at Medicine X, September 2012

Presented at Medicine X, September 2012

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Scaling Self-Experimentation Presentation Transcript

  • 1. Scaling Self-Experimentation IDA  SIM,  CO-­‐FOUNDER   September  28,  2012       A  project  of  the  Tides  Center     and  Professor  of  Medicine,   University  of  California  San  Francisco  
  • 2. n  =  1  
  • 3. (n  =  1).n  
  • 4. n  Σ (n  =  1).
  • 5. data  driven  feedback  loops  
  • 6. 2  
  • 7. without  better  sensemaking  to  drive  these  feedback  loops…  
  • 8. Plateau  of  Diminished  Promise  
  • 9. open  architecture  for  mobile  health   activity classification graphing mobility data over time a  small  set  of  common  principles/practices  by  which     these  modules  are  described  and  interface  to  one  another  
  • 10. enabling  reuse,  integration,  and  innovation     getting  further  together  faster…  
  • 11. n  Σ (n  =  1).
  • 12. does  caffeine  affect  my  sleep?   N-­‐of-­‐1  study  design   caffeine   no  caffeine   caffeine   sleep   sleep   no  caffeine   caffeine   no  caffeine  
  • 13. scaling  (n  =  1)  n  Outcome  Variables  •  a  caffeine  definition  module    •  a  sleep  definition  module,  with  APIs  for  getting  sleep  data  from   various  monitors  •  new  variables  that  take  advantage  of  mobile  (e.g.,  reality  mining)  Scripting  study  protocols  •  e.g.,  modules  for  setting  up  an  n-­‐of-­‐1  study    
  • 14. n   Σ scaling            (n=1)  Make  the  findings  comparable  for  aggregation  •  libraries  of  standard  measures  (e.g.,  PHQ-­‐9,  PROMIS)  •  indexing  of  variables  and  results  and  to  standard  vocabularies              
  • 15. n   Σ scaling            (n=1)  Need  to  describe  context  to  combine  apples  with  apples    •  who  is  “n”:  demographics,  important  clinical  features  •  study  approach:  ad  hoc,  n-­‐of-­‐1,  etc.    •  activity  context:  walking?  running?  •  social  context:  …  •  technical  context:  device,  operating  system,  app,  version,  sampling   rate…  •  etc.      
  • 16. 2  
  • 17. connect  with  us  •  Web:  www.openmhealth.org    •  Twitter:  @open_mhealth  •   email@openmhealth.org