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Agile Science and Teaching Behavior Change
- 1. Teaching Behavior Change: The baby steps for making effective behavioral interventions Eric Hekler, PhD School of Nutrition and Health Promotion Arizona State University May 16, 2012 Photo from Flickr - San Diego Shooter
- 2. We want interventions that are: Evidence-based Cost-effective Tailored Easy to disseminate Promote maintenance
- 3. 500,000th App Accepted on App Store 2005 2006 2007 2008 2009 2010 2011 2012 Conceive Submit Conduct the study of a study Grant Gather Receive Submit publications Pilot Data Funding for review Flickr – Metrix X
- 4. Making=Learning Flickr - San Diego Shooter
- 5. Empathizing=Understanding Flickr – Caro Wallis
- 6. Testing=Knowing Option 1 vs. Option 2 vs. Control Test by Sarah Kiser, Catherine Roland, Jesse Venzina
- 7. The Class Designing Behavior Change Interventions Grad class evidence-informed interventions Syllabus http://bit.ly/ASUhealthdesignclass See students work http://www.slideshare.net/DesigningHealth/
- 9. Class Projects Timeline wk1 wk4 wk6 wk18 Develop an SMS Use theory to Use previous work, theory, Focus health behavior make yourself and UX Design to iterate on a Intervention. healthier. health intervention. Who? Family & Self Targeted User Group Friends Baseline – Methods Pre/Post Iterate at least 3 times Comparison Intervention – Test with A vs B experiments Baseline Study
- 10. 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
- 11. Empathizing Trigger Make guitar easily accessible Put guitar in plain sight Simple Had to play one chord Positive Reinforcement Color calendar Before During Avgerage Intervention Intervention Increase Guitar 7% 40% 33% Serena Loeb’s DIY
- 12. Prototype 4: Testing De-stress your car SMS: “If you are stressed today, try one of the MOBILE following options, Deep CAR MAID Prototype 3: breathing, Stretching, get SERVICES up move around.” SMS Intervention GREEN CLEAN Prototype 2: Facial Wave S=Stop M=Move I= I statement; I can do it! Prototype 1: S.M.I.L.E. L=Love (positivity) E=Exhale Amy Luginbill; Samantha Quagliano; Sepideh Zohreh
- 13. Testing 10 8 Stress Level (0-10) 6 Pre 4 Post 2 0 Exp. P1 Exp. P2 Exp. P3 Exp. P4 Con. P1 Con. P2 -2
- 14. 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 Photo from Flickr - San Diego Shooter
- 15. 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 Photo from Flickr - San Diego Shooter
- 16. 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
- 17. 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
- 18. Thank you for your attention! Eric Hekler Designing Health Lab @ASU Twitter: @ehekler ehekler@asu.edu Syllabus: http://bit.ly/ASUhealthdesignclass See students work: http://www.slideshare.net/DesigningHealth/ Photo from Flickr - San Diego Shooter
Editor's Notes
- To quickly summarize a very large field of work, ultimately, we are trying to make interventions that are evidence-based, cost-effective, tailored, easy to disseminate, and promote maintenance. I have lots of experience with this, for example I’ve developed and have been testing in collaboration with Abby King and others here at Stanford some smartphone apps with the hopes of reaching this ideal.
- Science has been a very thoughtful and deliberative process.We move slowly to be “certain” we know something.We are moving so slowly, however, that we are making ourselves obsolete.Take for example the pace of science. Here is a typical timeline for a large NIH-funded grant (the gold-standard for health researchers).Compare this to the pace of technology companies moving.We need to do better and currently, our old ways of thinking about behavior change, including our old theories are frankly, not up to snuff to the challenges and opportunities that mHealth technologies allow us.
- Based on this, we need to move more into an open discussion in which we explore lots and lots of different ideas if we really want to understand which ones are best.Sadly, science, particularly behavioral science doesn’t really have the sort of “maker” culture that would allow us. As such, a key emphasis.
- If we are going to really move forward, we must also take lessons from user experience design with regard to fully emphathizing and feeling the problem of those we are trying to develop a solution for.
- Finally, it is very interesting that one of the more popular books in the Startup world is the Lean Startup, which basically argues for the scientific method within startups to ensure true learning. Classic in behavioral science, but as stated before we take too much time, particularly in early stages. BJ has been talking about a “crummy trial” which is a quick trial to learn the basic on if something is going to work.
- This brings me to the class I’ve been teaching at Arizona State University called Designing Health Behavior Change Interventions. It’s a grad-level class focused on teaching students how to develop evidence-informed apps. In the class, I attempt to integrate the best of behavioral science, user experience design, and rapid iterative design processes to teach students how to come up with the next generation of intervention ideas.
- As discussed earlier, the key areas of focus are learning how to empathize, make, and test ideas. Please note, these were health students and therefore, they focused on “making” experiences, not code.The First baby-step for starting this involves picking a theory, a particular user, or a riffing off of previous work. They give the foundation for making something.
- As suggested earlier though, I really wanted to push my students to make things as I felt that was the way for them to learn. In the first stage, I just wanted them to figure out how to take a theory and turn it into an intervention. As such, I assigned Cialidini’s work on persuasion and BJ”s Behavior Model and had them design.They then started basics on empathizing including interviewing, observation, surveying, etc. I also wanted them to “feel” what it was like to try and change a hard behavior and to link theory with an intervention. Hence, the DIY Health assignment. In the DIY Health study, they were assigned to use a within-person ABA study design to examine changes in themselves when they are or are not using an intervention. Soon after they started the DIY study, they then formed groups. The groups chose a target behavior, target group, and attempted to connect everything together. A key part of this was the use of experiments to test and confirm ideas.
- Students came up with some great ideas quickly within the SMS interventions. For example, Amy wanted to improve mood, so she explored providing prompts for smiling to others.The students explored a variety of topics such as sleep or reducing candy consumption.1st SMS, Friday January 20th: Happy Friday!! Psychologists have found that even a bad mood can be instantly lifted by forcing yourself to smile! Share the joy today, and smile at a stranger 2nd SMS, Saturday January 21st: It’s Saturday, smile 3rd SMS, Sunday January 22nd: Studies suggest people who smile more live longer! 4th SMS, Monday January 23rd: You are doing great! Keep it up!! Smiling is a great way to not only improve your appearance, but those who smile at others are perceived as more likeable, confident, conscientious, and stable! 5th SMS, Tuesday January 24th: No reminder 6th SMS, Wednesday January 25th: Good morning you gorgeous, smiling, radiant person! Did you know studies show people who smile often actually make more money than those who don’t? Big toothy grins = big paychecks! 7th SMS, Thursday January 26th: Final day of the 7-day smile challenge!! Smile today because you are truly a treasured friend, a kind and wonderful person, and a champion of this project!! Thank you all!! Last follow up text will be sent tonight, and results will be sent to you via email soon. CONGRATS!! :D
- The DIY experiments were really interesting as the students had to come up with something they forced them to better understand themselves and also figure out how to fix their own problems. They explored a variety of channels for this often with good success such as Serena’s Guitar intervention. She attempted to riff off of BJ’s baby steps SMS intervention to get herself to play more guitar. She felt that it fit in personal model of what was going wrong.
- The group studies were where the most interesting things happened. In particular, this was when the groups really took advantage of “crummy trials” for better understanding when an idea was working.For example, Amy, Sam, and Sepideh’s group was trying to reduce stress. They did a lot of empathizing work and looking into the previous literature to find the importance of breathing and stress management techniques. Sadly though, whenever they tested some of their ideas, which included mantras and other ideas to help simple triggers for relaxing, they all failed.This was particularly fascinating because in their initial brainstorming, they really loved their “S.M.I.L.E.” accronym that they came up with. When they tested it, comparing it to a control, it simply didn’t work.They perceived but ultimately found that they needed to pivot and instead ended up focusing on figuring out ways to de-stress a person’s environment. So they went and started cleaning cars and got great responses.
- This was from the test of their final prototype idea on a self-reported measure of stress.All of the intervention group reduced their stress whereas the control stayed the same or increased stress. This suggested a good pivot in the right direction. They figured this out in 4 weeks and would likely never have gotten here without the testing as they really loved their initial ideas and would not be able to hear counter ideas without the data.