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Eric Hekler, PhDSchool of Nutrition and Health Promotion
Arizona State University
May 16, 2012
Teaching Behavior Change:
The baby steps for making effective behavioral interventions
Photo from Flickr - San Diego Shooter
We want interventions that are: Evidence-based
Cost-effective
Tailored
Easy to disseminate
Promote maintenance
Flickr – Metrix X
2005 2006 2007 2008 2009 2010 2011 2012
Conceive of a study
Gather Pilot Data
Submit Grant
Receive Funding
Conduct the study
Submit publications for review
500,000th AppAccepted on App Store
Flickr - San Diego Shooter
Making=Learning
Flickr – Caro Wallis
Empathizing=Understanding
Option 1
Option 2
Control
Testing=Knowing
vs.
vs.
Test by Sarah Kiser, Catherine Roland, Jesse Venzina
The Class
Designing Behavior Change Interventions
Grad class evidence-informed interventions
Syllabushttp://bit.ly/ASUhealthdesignclass
See students workhttp://www.slideshare.net/DesigningHealth/
Class Projects Timeline
SMS Intervention
wk1 wk4 wk6
DIY Health Study
Group Project Starts
wk18
Foc
usM
etho
dsW
ho?
Develop an SMS health behavior Intervention.
Use theory to make yourself healthier.
Use previous work, theory, and UX Design to iterate on a health intervention.
Family & Friends
Self Targeted User Group
Pre/PostComparison
Baseline – Intervention – Baseline Study
Iterate at least 3 timesTest with A vs B experiments
Making
Intervention: “Genuinely smile at one stranger a day. If you already smile at people, make it a big toothy grin.”
Procedure: Morning SMS,
Evening Measurement SMS.
Amy Luginbill’s SMS project
Empathizing Trigger
Make guitar easily accessible Put guitar in plain sight
Simple Had to play one chord
Positive Reinforcement Color calendar
Before Intervention
During Intervention
AvgerageIncrease
Guitar 7% 40% 33% Serena Loeb’s DIY
Amy Luginbill; Samantha Quagliano; Sepideh Zohreh
S=StopM=MoveI= I statement; I can do it!L=Love (positivity)E=Exhale
SMS: “If you are stressed today, try one of the following options, Deep breathing, Stretching, get up move around.”
MOBILE CAR MAID SERVICES
GREEN CLEAN
Prototype 1: S.M.I.L.E.
Prototype 2:Facial Wave
Prototype 3:SMS Intervention
Prototype 4:De-stress your car
Pivot
Testing
Testing
Exp. P1 Exp. P2 Exp. P3 Exp. P4 Con. P1 Con. P2
-2
0
2
4
6
8
10
PrePost
Str
es
s L
ev
el
(0-1
0)
Summary
Current evaluation methods are too slow Behavioral theories cannot fully explain
mHealth data To realize the potential of mHealth technology
Start from a wide array of ideas to learn HOW mHealth technologies work.
utilize “baby steps” for rapid iteration of making, empathizing & testing
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Do as quickly as possible
Pick a reference: theory, user, or previous work Explore multiple ideas Make something Identify assumptions
“What else is true?” Test assumptions with a “crummy trial” Repeat
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Agile Science – beta
Explore time-effective funding channels
Emphasize time-effectiveness of methods
Create, test, & iterate MVPs
Use a variety of dissemination channels
Use business to disseminate
Thanks to my fantastic students
Sarah Kiser
Serena Loeb
Amy Luginbill
Nathanael Meckes
Samantha Quagliano
Catherine Roland
Jesse Sandvik
Brooke Schohl
Jesse Venzina
Sepideh Zohreh
Photo from Flickr - San Diego Shooter
Thank you for your attention!
Eric Hekler
Designing Health Lab @ASU
Twitter: @ehekler
Syllabus: http://bit.ly/ASUhealthdesignclass
See students work: http://www.slideshare.net/DesigningHealth/
Photo from Flickr - San Diego Shooter