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The Exercise Research Behind Peloton’s Success

October 4, 2021

The Science Behind the Science of Change

The Science of Change is a new podcast hosted by behavioral scientist and co-founder of Irrational Labs, Kristen Berman. On this show, Kristen chats with visionary product and organizational leaders to uncover their insights about user behavior — and how they’ve managed to change it. For listeners who want a deeper dive into the behavioral science behind each episode, we’ve compiled and summarized the most relevant research here.

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How long does it take to form an exercise habit?

Surprisingly, there’s not a whole lot of data on this out there. The best study we have is a longitudinal study of gym habit formation in Canada. They find that exercise habits mostly formed after working out at least 4 times a week for 6 weeks. However, they measured habits using self-reported (not actual) behavioral automaticity (for example “when I exercise, I do it automatically,” on a 1-5 scale).

(Perceived) action complexity influenced the speed of habit formation: exercise routines that felt simpler turned into habits faster than those that felt complicated. But note that this study didn’t objectively evaluate routines, it just asked people to report how effortful the routine felt.

The 6-week estimate is fairly close to what another study found: a median time to achieve habit formation was about 9 weeks (66 days). This second study looked at a number of health behaviors (such as drinking a glass of water with breakfast) and not just exercise. Accordingly, there was considerable variability, and researchers found that habit formation thresholds ranged anywhere from 18 days to 254(!).

In any case, both of these estimates are way longer than the conventional wisdom of “21 days to form a habit.” Fun anecdote: The 21-day rule of thumb started from Maxwell Maltz, a plastic surgeon who wrote a self-help book in the 1960’s. He noted that people take at least 21 days after plastic surgery to get used to their new face. Decades later, a game of telephone transformed this observation into a supposed law of habit.

Should you try to always work out at the same time/place?

Based on what we know about habits, to form a habit, you want to repeat an action at a consistent setting. For example, you might aim to exercise first thing in the morning, or right after work. This approach, habit stacking, should presumably yield stronger habits compared with working out at random times. We assume this is true because there’s significant evidence demonstrating the role of consistency in habit, but comparatively less good data about exercise specifically.

  • In support, there is some data showing that people who work out at regular times exercise more and have stronger exercise habits, although most studies are of so-so quality (cross-sectional surveys). The one solid, longitudinal study supporting this argument is the Canadian study mentioned above.
  • On the other hand, there was a large study that paid people to either exercise whenever, or exercise during a specific 2-hour window. The “2-hour window” group exercised less than the “exercise-whenever” group.
  • The main issue with the supporting studies is that they are not experimental. You can’t rule out the possibility that people who work out at the same time each day are also more committed, conscientious, or have another characteristic that makes it more likely that they would have persisted anyway. Nor does it account for the variable conditions of lifestyle, like a stable home environment that would free up more time to exercise. Maybe there’s nothing magical about these people, and they actually have more stable or controllable environments (their own house, access to childcare, etc.) that make it easier for them to work out regularly.
  • One limitation of the opposing study is that it’s a single (albeit well-done) study on Google employees. But more importantly, it experimentally manipulated incentivizing people to work out at a specific window vs. not, which is not the same as having them work out regularly vs. not. It could be that when someone is paid to work out between 7-9 am and misses that window, they give up on going to the gym that day altogether, whereas someone who just has a habit of going in the morning is still able to act flexibly and go later that day if needed.  
  • A related issue is the outstanding question on how to define consistency. Using an objective 2-hour window may be necessary for an unambiguous criterion—but people can have more fluid cues like “after work,” which is psychologically constant but can fall at different times on different days. 

 

What has an impact on a person’s exercise habits? The real habit to focus on might be preparing to exercise

Exercise is a complex behavior—it involves multiple steps. For example, to go to the gym, you might first need to:  1) Put on your gym clothes, 2) Gather a second set of clothes, 3) Pack this second set of clothes in a gym bag, 4) Walk to a bus station, 5) Ride the bus, and 6) Get off and then walk to the gym. Each additional step on the way to a behavior poses another opportunity for drop off.

In line with this intuition, some research suggests that automatically prepping for exercise may be more important than automatically performing an exercise routine. When a person repeats the same exercise routine until they can finally go through it automatically, it becomes a habit.

This study measured gym patrons’ habit strength for (a) prepping to exercise, and (b) exercising, and then measured their actual exercise 6 weeks later (self-reported, but using the Godin scale, which has been validated against objective measures before). They found that strong preparation habits predicted higher levels of exercise, but performance habits did not.

A related study encouraged some participants to fill half their dinner plates with fruits and veggies and then followed them for 3 weeks, where participants submitted photos of their dinner plates. Participants in the treatment group formed a strong habit despite using a variety of ways to eat more fruits and veggies (for example eating a banana with breakfast, adding veggies to a noodle dish, etc.). 

These findings are key to solving a basic dilemma in exercise: Should you keep workouts the same (to foster habit formation), or should you constantly change things up (to keep things interesting and stoke intrinsic motivation)?

Based on this research, the secret might be in automating the initiation but varying the workout. This is especially relevant to home workouts, since, unlike traditional workouts where varying might require some thinking, home workouts could vary the type of workout presented to a user without requiring extra effort from the user. 

Do habits break when you miss a day or two?

Not really. One of the studies mentioned above had participants track the performance and perceived automaticity of a new health behavior over several months. Missing a single day (but returning to perform the behavior the following day) did not influence habit formation.

This contradicts the streak-based “don’t break the chain” concept that permeates a ton of so-called habit formation apps: Given that missed days don’t seem to harm habit formation, striving for perfect adherence might backfire by producing a “what the hell” effect, where a single missed day causes further non-adherence (see some examples in diet).

Longer breaks, on the other hand, might have a detrimental effect on habit formation. For example, this study of Danish fitness centers found that gym attendance fell from about 2 times a week on average before Easter break, to about 1.7 times a week after. Their data showed no rebounding effect with time: Weekly gym visits actually continue to decline in the 10 weeks following Easter, down to 1.3 times a week. Worryingly, the harmful effects of Easter break were much more pronounced for people with strong habits (those who went to the gym at least twice a week before the holiday).

Why can some people always get out of bed and go on a run?

They have a stronger habit. This means if one day their intentions are weaker, their habit drive will override. For most of us without strong habit—if we have low intentions to work out, we just won’t. “On days when people had intentions that were weaker than typical for them, habit strength was positively related to physical activity, but on days when people had typical or stronger intentions than was typical for them, habit strength was unrelated to daily physical activity.

 

Exercise is not known for being an effective way of reducing weight

This Vox article does a great job of presenting the evidence for this argument. I like the graphic that they include (below), illustrating that two margaritas can undo even an intense workout (burning 700 calories).

Diet alone seems to be more effective than exercise alone, potentially because our bodies respond to exercise by burning fewer calories, offsetting the calories burned during a workout. This metabolic adaptation also happens in response to diet, but apparently not as much.

But even if you take the stance that exercise isn’t a good way to lose weight, exercise is still the cure for pretty much everything else (blood pressure, stress, improved mental health and mental functioning, etc.) This is a comprehensive review.

Image Source: Javier Zarracina, VOX

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Want to dive deeper into the research discussed in the episode? 

Freedman, J. L., & Fraser, S. C. (1966). Compliance without pressure: The foot-in-the-door technique. Journal of Personality and Social Psychology, 4(2), 195–202. https://doi.org/10.1037/h0023552

Bateson, M., Callow, L., Holmes, J. R., Redmond Roche, M. L., & Nettle, D. (2013). Do images of ‘watching eyes’ induce behaviour that is more pro-social or more normative? A field experiment on littering. PloS one, 8(12), e82055. https://doi.org/10.1371/journal.pone.0082055

Kelsey, C., Vaish, A., & Grossmann, T. (2018). Eyes, More Than Other Facial Features, Enhance Real-World Donation Behavior. Human nature (Hawthorne, N.Y.), 29(4), 390–401. https://doi.org/10.1007/s12110-018-9327-1

Ahearn, A. (2019). Moving From 5% to 85% Completion Rates for Online Courses. EdSurge. https://www.edsurge.com/news/2019-06-06-moving-from-5-to-85-completion-rates-for-online-courses

Renfree, I., Harrison, D., Marshall, P., Stawarz, K., & Cox, A.L. (2016). Don’t Kick the Habit: The Role of Dependency in Habit Formation Apps. Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems. https://dl.acm.org/doi/10.1145/2851581.2892495

Gollwitzer, P. M., & Brandstätter, V. (1997). Implementation intentions and effective goal pursuit. Journal of Personality and Social Psychology, 73(1), 186–199. https://doi.org/10.1037/0022-3514.73.1.186

Milkman, K. L., Beshears, J., Choi, J. J., Laibson, D., & Madrian, B. C. (2011). Using 

implementation intentions prompts to enhance influenza vaccination rates. Proceedings of the National Academy of Sciences of the United States of America, 108(26), 10415–10420. https://doi.org/10.1073/pnas.1103170108

Nickerson, D. W., & Rogers, T. (2010). Do You Have a Voting Plan? Implementation Intentions, Voter Turnout, and Organic Plan Making. Psychological Science, 21(2), 194–199. http://www.jstor.org/stable/41062187

O’Donoghue, T., & Rabin, M. (1999). Doing it now or later. American Economic Review, 89(1), 103-124.

Schumacher, L. M., Thomas, J. G., Raynor, H. A., Rhodes, R. E., O’Leary, K. C., Wing, R. R., & Bond, D. S. (2019). Relationship of Consistency in Timing of Exercise Performance and Exercise Levels Among Successful Weight Loss Maintainers. Obesity (Silver Spring, Md.), 27(8), 1285–1291. https://doi.org/10.1002/oby.22535

Tappe, K., Tarves, E., Oltarzewski, J., & Frum, D. (2013). Habit formation among regular exercisers at fitness centers: an exploratory study. Journal of physical activity & health, 10(4), 607–613. https://doi.org/10.1123/jpah.10.4.607

Berger-Tal, O., Nathan, J., Meron, E., & Saltz, D. (2014). The exploration-exploitation dilemma: a multidisciplinary framework. PloS one, 9(4), e95693. https://doi.org/10.1371/journal.pone.0095693

Elbel, B., Kersh, R., Brescoll, V. L., & Dixon, L. B. (2009). Calorie labeling and food choices: a first look at the effects on low-income people in New York City. Health affairs (Project Hope), 28(6), w1110–w1121. https://doi.org/10.1377/hlthaff.28.6.w1110

Karlan, D.S., Morten, M., Morten, M., & Zinman, J. (2012). A Personal Touch: Text Messaging for Loan Repayment. Randomized Social Experiments eJournal.

 

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