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Healthier Together: Social
Approaches to Health and Wellness
           Paul Resnick
Outline
• My Story
  – Collaborations with people who had
    complementary expertise
• Advice
• Social Nudges for Health Behavior
MY STORY
College
• Math SB, 1985
Grad School
• Computer Science, SM 1988, PhD 1992
LEARNING FROM COLLABORATIONS
Community
     Development




Mel King
Human Factors



                Bob Virzi
Distributed Systems




                      John Riedl
Law and Policy




             Larry Lessig
Political Science




Bob Putnam             Brendan Nyhan
Saguaro Seminar 1997
Saguaro Seminar 1997
Saguaro Seminar 1997
Saguaro Seminar 1997
Economics




            Richard
            Zeckhauser
Economics




            Eric Friedman
Computer Science Theory




Rahul Sami
Social Psychology




Bob Kraut                Sara Kiesler
CommunityLab
Advice
• Collaborate with complementary experts
• Go deep in fields you cross into
  – (not necessarily broad)
• Learn math and programming in grad school
• Theory, Practice, and the Design Perspective
Wisdom from Kurt Lewin

“There is nothing so practical
as a good theory”


“If you want to understand
something, try to change it”
Advice
• Collaborate with complementary experts
• Go deep in fields you cross into
  – (not necessarily broad)
• Learn math and programming in grad school
• Understand      Change
SOCIAL NUDGES FOR HEALTH
BEHAVIOR CHANGE
THE OBESITY EPIDEMIC
Costs of Obesity
• In human terms
  – Heart disease
  – Stroke
  – Type 2 diabetes
• In economic terms
  – $147 billion estimated in 2008
  – Mean $1,429/person per year more than normal
    weight
Obesity Trends* Among U.S. Adults
                             BRFSS, 1985
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%
Obesity Trends* Among U.S. Adults
                             BRFSS, 1986
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%
Obesity Trends* Among U.S. Adults
                             BRFSS, 1987
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4”
                 person)




No Data   <10%      10%–14%
Obesity Trends* Among U.S. Adults
                             BRFSS, 1988
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%
Obesity Trends* Among U.S. Adults
                             BRFSS, 1989
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%
Obesity Trends* Among U.S. Adults
                             BRFSS, 1990
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%
Obesity Trends* Among U.S. Adults
                             BRFSS, 1991
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%
Obesity Trends* Among U.S. Adults
                             BRFSS, 1992
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%
Obesity Trends* Among U.S. Adults
                             BRFSS, 1993
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%
Obesity Trends* Among U.S. Adults
                             BRFSS, 1994
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%
Obesity Trends* Among U.S. Adults
                             BRFSS, 1995
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%
Obesity Trends* Among U.S. Adults
                             BRFSS, 1996
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%
Obesity Trends* Among U.S. Adults
                             BRFSS, 1997
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%    ≥20%
Obesity Trends* Among U.S. Adults
                             BRFSS, 1998
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%    ≥20%
Obesity Trends* Among U.S. Adults
                             BRFSS, 1999
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%    ≥20%
Obesity Trends* Among U.S. Adults
                             BRFSS, 2000
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%    ≥20%
Obesity Trends* Among U.S. Adults
                             BRFSS, 2001
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%    20%–24%   ≥25%
Obesity Trends* Among U.S. Adults
                            BRFSS, 2002
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%    20%–24%   ≥25%
Obesity Trends* Among U.S. Adults
                             BRFSS, 2003
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%    20%–24%   ≥25%
Obesity Trends* Among U.S. Adults
                             BRFSS, 2004
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%    20%–24%   ≥25%
Obesity Trends* Among U.S. Adults
                             BRFSS, 2005
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%    20%–24%   25%–29%    ≥30%
Obesity Trends* Among U.S. Adults
                             BRFSS, 2006
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%    20%–24%   25%–29%    ≥30%
Obesity Trends* Among U.S. Adults
                             BRFSS, 2007
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%    20%–24%   25%–29%    ≥30%
Obesity Trends* Among U.S. Adults
                             BRFSS, 2008
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%    20%–24%   25%–29%    ≥30%
Obesity Trends* Among U.S. Adults
                             BRFSS, 2009
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%    20%–24%   25%–29%    ≥30%
Obesity Trends* Among U.S. Adults
                             BRFSS, 2010
                 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)




No Data   <10%      10%–14%    15%–19%    20%–24%   25%–29%    ≥30%
HealthierTogether.info
Collaborators
•   Caroline Richardson   • Sean Munson
•   Mark Newman           • Debra Lauterbach
•   Margaret Morris
•   Erin Krupka
SELF-TRACKING



The Quantified Self
Sleep
Physical Activity
Food
Moods
+ Gamification (Points + Levels)
THE POWER OF SHARING
BEHAVIOR CHANGE:
MAKING ACTIVITY FUN
Team Quests




Buis, L., T. Poulton, R. Holleman, A. Sen, P. Resnick, D. Goodrich, L. Palma-Davis and C.
Richardson (2009). "Evaluating Active U: an internet-mediated physical activity program."
BMC Public Health 9(1): 331.
Making the Behavior Social
Making the Tracking Social
• Richardson et al
• J Med Internet Res
  2010;12(4):e71
• Individual tracking
  only
   – 66% completed program
• With forums
   – 79% completed
• Same step count
  increases
   – 4468   6948 per day
BEHAVIOR CHANGE:
MAKING ACTIVITY REWARDING
Encouragement from Others: Nike+
Helping Others
• Helping others may be very motivating
• Study design
  – Obese teens
  – Gift cards for completing walking goals
     • You
     • A friend you pick
     • Split between you and friend
BEHAVIOR CHANGE:
ACCOUNTABILITY TO OTHERS
Feedback from Others
Accountability: Interventions
• OneRecovery
Accountability: Monitors
• Stickk
Accountability: Social Punishments
• Steps Commitments
DETOUR: POWER ANALYSIS AND
EXPERIMENT DESIGN
Experimental Conditions: 2x2
•   Private commitments and results
•   Public commitments; private results
•   Private commitments; public results
•   Public commitments; public results
Design 1: Between Subjects
• Each subject randomly assigned to one
  condition
• Stay in the that condition for 14 weeks
• Analysis: more walking in some conditions
  than others?
Power Analysis via Simulation
• Each of K times, run a simulated experiment with n
  subjects
   – For each subject
      • Draw results from an assumed distribution
          – (e.g., condition 2 has 500 steps/day more on average than condition 1;
            some assumed variance between people, between days)
   – Run data analysis on the dataset
      • Record whether difference between conditions is statistically
        significant or not
• Power = percentage of simulated experiments with
  significant results
• Try different values for n, to see how many subjects
  you need
Design 1: Between Subjects
• Each subject randomly assigned to one
  condition
• Stay in the that condition for 14 weeks
• Analysis: more walking in some conditions
  than others?
• Power analysis: even 90 subjects per condition
  not enough!
Design 2: Partially Within-Subjects
                Design
• Each subject starts with a no commitments
  baseline for a few weeks
• Then randomly assigned to one of the four
  conditions
• Analysis: compare difference from baseline,
  between conditions
  – Factors our individual
• Power analysis: 65 subjects per condition
  90% power
BARRIERS TO OVERCOME
Embarrassment
“I got people, you know, from my high school
that I am friends with that I haven't talked to
in 25 years. And I have no desire for them to
know about my weight issues or weight status.”

“… I did not put that on because I didn't want
everybody on Facebook knowing that my butt
muscle hurt today.”
Newman, M. W., D. Lauterbach, S. A. Munson, P. Resnick and M. E. Morris (2011). It's not
that i don't have problems, I'm just not putting them on Facebook: challenges and
opportunities in using online social networks for health. Proceedings of the ACM 2011
conference on Computer supported cooperative work. Hangzhou, China, ACM: 341-350.
Spamming
“…mostly when I make things private, it’s more
because I think they’d be boring or
insignificant to my friends, not because they’re
actually things I wouldn’t want my
friends to know about. I just don’t want to clog up
their Facebook with it.”

Munson, S., D. Lauterbach, M. Newman and P. Resnick (2010). Happier
Together: Integrating a Wellness Application into a Social Network Site.
Persuasive Technology. T. Ploug, P. Hasle and H. Oinas-Kukkonen, Springer
Berlin / Heidelberg. 6137: 27-39.
Comparison and Competition
                 Avoidance
• Comparisons can demotivate
• Some people avoid them
• Active U
    – 1 point increase in BMI 1% decrease in
      likelihood to join a team

Buis, L., T. Poulton, R. Holleman, A. Sen, P. Resnick, D. Goodrich, L. Palma-
Davis and C. Richardson (2009). "Evaluating Active U: an internet-mediated
physical activity program." BMC Public Health 9(1): 331.
Unhelpful Responses
• “Oh, you are counting calories? That will never
  work, you have to count carbs/fat/fiber etc...”
• “Oh, come on, it's a birthday party, you can
  have ONE piece of cake...”
• “Oh, you're fine the way you are, your
  husband loves you anyway, why put yourself
  through this?”
From
http://www.sparkpeople.com/resource/article_comments.asp?id=87&type=1
Summary
• Benefits of tracking together
  – Behavior change
  – (Support)
  – (Decision-making)
• Design Challenges
  – Sharing the right stuff with the right people
  – Matching social elements to individual needs
Conclusion
• Advice
  – Collaborate with complementary experts
  – Go deep in fields you cross into
  – Learn math and programming in grad school
  – Understand        Change

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Paul Resnick, "Healthier Together: Social Approaches to Health and Wellness"

  • 1. Healthier Together: Social Approaches to Health and Wellness Paul Resnick
  • 2. Outline • My Story – Collaborations with people who had complementary expertise • Advice • Social Nudges for Health Behavior
  • 5. Grad School • Computer Science, SM 1988, PhD 1992
  • 7. Community Development Mel King
  • 8. Human Factors Bob Virzi
  • 9. Distributed Systems John Riedl
  • 10. Law and Policy Larry Lessig
  • 16.
  • 17. Economics Richard Zeckhauser
  • 18. Economics Eric Friedman
  • 22.
  • 23. Advice • Collaborate with complementary experts • Go deep in fields you cross into – (not necessarily broad) • Learn math and programming in grad school • Theory, Practice, and the Design Perspective
  • 24.
  • 25. Wisdom from Kurt Lewin “There is nothing so practical as a good theory” “If you want to understand something, try to change it”
  • 26. Advice • Collaborate with complementary experts • Go deep in fields you cross into – (not necessarily broad) • Learn math and programming in grad school • Understand Change
  • 27. SOCIAL NUDGES FOR HEALTH BEHAVIOR CHANGE
  • 29. Costs of Obesity • In human terms – Heart disease – Stroke – Type 2 diabetes • In economic terms – $147 billion estimated in 2008 – Mean $1,429/person per year more than normal weight
  • 30. Obesity Trends* Among U.S. Adults BRFSS, 1985 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14%
  • 31. Obesity Trends* Among U.S. Adults BRFSS, 1986 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14%
  • 32. Obesity Trends* Among U.S. Adults BRFSS, 1987 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14%
  • 33. Obesity Trends* Among U.S. Adults BRFSS, 1988 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14%
  • 34. Obesity Trends* Among U.S. Adults BRFSS, 1989 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14%
  • 35. Obesity Trends* Among U.S. Adults BRFSS, 1990 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14%
  • 36. Obesity Trends* Among U.S. Adults BRFSS, 1991 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19%
  • 37. Obesity Trends* Among U.S. Adults BRFSS, 1992 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19%
  • 38. Obesity Trends* Among U.S. Adults BRFSS, 1993 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19%
  • 39. Obesity Trends* Among U.S. Adults BRFSS, 1994 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19%
  • 40. Obesity Trends* Among U.S. Adults BRFSS, 1995 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19%
  • 41. Obesity Trends* Among U.S. Adults BRFSS, 1996 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19%
  • 42. Obesity Trends* Among U.S. Adults BRFSS, 1997 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% ≥20%
  • 43. Obesity Trends* Among U.S. Adults BRFSS, 1998 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% ≥20%
  • 44. Obesity Trends* Among U.S. Adults BRFSS, 1999 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% ≥20%
  • 45. Obesity Trends* Among U.S. Adults BRFSS, 2000 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% ≥20%
  • 46. Obesity Trends* Among U.S. Adults BRFSS, 2001 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% ≥25%
  • 47. Obesity Trends* Among U.S. Adults BRFSS, 2002 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% ≥25%
  • 48. Obesity Trends* Among U.S. Adults BRFSS, 2003 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% ≥25%
  • 49. Obesity Trends* Among U.S. Adults BRFSS, 2004 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% ≥25%
  • 50. Obesity Trends* Among U.S. Adults BRFSS, 2005 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  • 51. Obesity Trends* Among U.S. Adults BRFSS, 2006 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  • 52. Obesity Trends* Among U.S. Adults BRFSS, 2007 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  • 53. Obesity Trends* Among U.S. Adults BRFSS, 2008 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  • 54. Obesity Trends* Among U.S. Adults BRFSS, 2009 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  • 55. Obesity Trends* Among U.S. Adults BRFSS, 2010 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  • 57. Collaborators • Caroline Richardson • Sean Munson • Mark Newman • Debra Lauterbach • Margaret Morris • Erin Krupka
  • 59. Sleep
  • 61. Food
  • 62. Moods
  • 64. THE POWER OF SHARING
  • 66. Team Quests Buis, L., T. Poulton, R. Holleman, A. Sen, P. Resnick, D. Goodrich, L. Palma-Davis and C. Richardson (2009). "Evaluating Active U: an internet-mediated physical activity program." BMC Public Health 9(1): 331.
  • 68. Making the Tracking Social • Richardson et al • J Med Internet Res 2010;12(4):e71 • Individual tracking only – 66% completed program • With forums – 79% completed • Same step count increases – 4468 6948 per day
  • 71. Helping Others • Helping others may be very motivating • Study design – Obese teens – Gift cards for completing walking goals • You • A friend you pick • Split between you and friend
  • 77. DETOUR: POWER ANALYSIS AND EXPERIMENT DESIGN
  • 78. Experimental Conditions: 2x2 • Private commitments and results • Public commitments; private results • Private commitments; public results • Public commitments; public results
  • 79. Design 1: Between Subjects • Each subject randomly assigned to one condition • Stay in the that condition for 14 weeks • Analysis: more walking in some conditions than others?
  • 80. Power Analysis via Simulation • Each of K times, run a simulated experiment with n subjects – For each subject • Draw results from an assumed distribution – (e.g., condition 2 has 500 steps/day more on average than condition 1; some assumed variance between people, between days) – Run data analysis on the dataset • Record whether difference between conditions is statistically significant or not • Power = percentage of simulated experiments with significant results • Try different values for n, to see how many subjects you need
  • 81. Design 1: Between Subjects • Each subject randomly assigned to one condition • Stay in the that condition for 14 weeks • Analysis: more walking in some conditions than others? • Power analysis: even 90 subjects per condition not enough!
  • 82. Design 2: Partially Within-Subjects Design • Each subject starts with a no commitments baseline for a few weeks • Then randomly assigned to one of the four conditions • Analysis: compare difference from baseline, between conditions – Factors our individual • Power analysis: 65 subjects per condition 90% power
  • 84. Embarrassment “I got people, you know, from my high school that I am friends with that I haven't talked to in 25 years. And I have no desire for them to know about my weight issues or weight status.” “… I did not put that on because I didn't want everybody on Facebook knowing that my butt muscle hurt today.” Newman, M. W., D. Lauterbach, S. A. Munson, P. Resnick and M. E. Morris (2011). It's not that i don't have problems, I'm just not putting them on Facebook: challenges and opportunities in using online social networks for health. Proceedings of the ACM 2011 conference on Computer supported cooperative work. Hangzhou, China, ACM: 341-350.
  • 85. Spamming “…mostly when I make things private, it’s more because I think they’d be boring or insignificant to my friends, not because they’re actually things I wouldn’t want my friends to know about. I just don’t want to clog up their Facebook with it.” Munson, S., D. Lauterbach, M. Newman and P. Resnick (2010). Happier Together: Integrating a Wellness Application into a Social Network Site. Persuasive Technology. T. Ploug, P. Hasle and H. Oinas-Kukkonen, Springer Berlin / Heidelberg. 6137: 27-39.
  • 86. Comparison and Competition Avoidance • Comparisons can demotivate • Some people avoid them • Active U – 1 point increase in BMI 1% decrease in likelihood to join a team Buis, L., T. Poulton, R. Holleman, A. Sen, P. Resnick, D. Goodrich, L. Palma- Davis and C. Richardson (2009). "Evaluating Active U: an internet-mediated physical activity program." BMC Public Health 9(1): 331.
  • 87. Unhelpful Responses • “Oh, you are counting calories? That will never work, you have to count carbs/fat/fiber etc...” • “Oh, come on, it's a birthday party, you can have ONE piece of cake...” • “Oh, you're fine the way you are, your husband loves you anyway, why put yourself through this?” From http://www.sparkpeople.com/resource/article_comments.asp?id=87&type=1
  • 88. Summary • Benefits of tracking together – Behavior change – (Support) – (Decision-making) • Design Challenges – Sharing the right stuff with the right people – Matching social elements to individual needs
  • 89. Conclusion • Advice – Collaborate with complementary experts – Go deep in fields you cross into – Learn math and programming in grad school – Understand Change