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
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%
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
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
