Putting a new spin on behavior change

So you got a Fitbit for Christmas and you were psyched. New year, new me, you thought. Time to pump up the jams and get down to business. And for most of January, you did — consistently hitting that 10,000-step goal and feeling like a champ.

Then came February, and instead of delivering a heart-shaped Valentine’s Day surprise, your beloved broke yours. Suddenly, even 5,000 steps a day seemed impossible. Gradually, you got back to your old self and started hitting that 10,000-step goal again.

Until bam! An April Fool’s Day prank gone wrong had you laid up for a month with a bum leg and down went your progress again. Now it’s late May and you’re seriously considering chucking that sleek, high-tech reminder of your failures and inadequacies into Tempe Town Lake to swim with the fishes.

Most health experts would agree, the rise in popularity of fitness trackers is a good thing overall. People all around the globe are feeling more motivated to be active and enjoying the agency that comes with being in control of their own health.

But one of the big caveats of favored devices like Fitbits is they take a one-size-fits-all approach that doesn’t account for the sometimes subtle and nuanced tweaks needed for real behavior change, and that can leave people feeling disappointed in themselves, or worse, cause them to give up altogether.

Video by Deanna Dent/ASU Now

“A lot of the behavioral interventions that have been designed set fixed goals,” said Marc Adams, associate professor in Arizona State University’s College of Health Solutions. “You either make that bar or you don’t. If your goal is always 10,000 steps, and you just can’t reach that because there’s too much going on in your life, imagine how disappointing or frustrating it would be.”

Determined to find a better way, Adams and his team at the College of Health Solutions designed a behavior intervention called WalkIT Arizona that accounts for the ups and downs of daily life, meeting individuals where they’re at using adaptive goal setting.

“What’s neat about adaptive goals is that the goals are not a threshold, they’re not a trajectory you need to follow up. They mold to the participants,” he said. “So sometimes they’ll be a little higher, sometimes they’ll be a little lower. And it all depends, because we all work, we all travel, we all have illnesses. We have major life events like marriages, divorces, personal health issues, children. And all of those things affect our physical activity, and our interventions should try and account for those things.”

Adams and his team recruited 500 insufficiently active adults from all over the Valley and gave them a wearable fitness monitor to wear for one year to test the effectiveness of adaptive goals versus static goals, as well as immediate rewards versus delayed rewards.

In addition, the researchers also took into account the effect of participants’ built environment, analyzing the entirety of Maricopa County to identify areas of high walkability and areas of low walkability. Similar existing research has looked only at the relationship between where people live and their current activity habits, without applying a behavioral intervention and following them over time to measure its effect.

“Our hypothesis is that if you’re insufficiently active to start but you live in an environment that supports physical activity and you get a treatment — a behavioral intervention to make you go out and be active — that because your environment is supportive of your activity, you’ll be more likely to continue with that activity compared to someone who gets a behavioral intervention whose environment is not supportive of their activity,” Adams explained.

The research is in line with recent updates to the national Physical Activity Guidelines, a set of recommendations that impact public health policies, that featured new insights into behavior change interventions, wearables and the built environment.

Over the course of one year, participants receive updates on their daily goals via text messages. Those randomized into the static goals group receive the same goal of 10,000 steps every day. Those randomized into the adaptive goals group receive a different step goal each day, determined by an algorithm that bases it on their past progress.

All the data collected by the fitness monitor is synced to participants’ phones and sent to Adams and his team, who determine whether or not they’ve earned a reward for the day.

The hope is that adaptive goal setting will allow participants’ physical activity regimens to be more sustainable and consistent over time.

“It’s like a good coach,” Adams said. “A good coach would figure out where you’re at and work with you to get to the target that you’re both interested in.”

The study is ongoing, with an expected conclusion time frame of August 2021.

Top photo: College of Health Solutions Associate Professor Marc Adams. Photo by Deanna Dent/ASU Now