A few years ago, I decided I wanted to make cycling my primary mode of transportation. I knew about the many benefits of cycling to work: I would save money, lower my carbon footprint, get more exercise, and increase productivity by combining exercise with my daily commute. Still, I struggled to make the change. Why was it so difficult? It’s hard to change our habits; it requires conscious efforts to break down those learned behavioral patterns. Not to mention the fundamental challenges associated with learning a new behavior.
It took me a few years but I have now become a habitual cyclist. Looking back, I recognize two factors that helped increase my motivation and make me more confident in my ability to change. First, I got my gear shifter fixed so that I could face the steep hills on my way to work. This removed a physical barrier, and instantly made my goal feel more attainable. Second, I learned about a bike map prepared by the local government that highlights the best bike routes. When travelling by car, we often use the most direct routes, but those are often not the safest — nor are they necessarily the fastest — for cyclists. I found a route with low vehicle traffic, bike lanes, and pedestrian- and cyclist-controlled traffic lights, allowing me to reach my destination safely, and as quickly as my previous bus commute.
Behavioral Science, Democratized
We make 35,000 decisions each day, often in environments that aren’t conducive to making sound choices.
At TDL, we work with organizations in the public and private sectors—from new startups, to governments, to established players like the Gates Foundation—to debias decision-making and create better outcomes for everyone.
Change is a process
Research in health and environmental psychology suggest that behavior-change occurs in a series of stages. Would a bike map have facilitated long-term behavior-change if I didn’t already feel motivated? What if I hadn’t already fixed my bike? Probably not, because I wouldn’t have been in the right stage.Stage-based models provide tools to help guide behavioral transitions.
Essentially, stage-based models suggest that changing day-to-day behavior happens in three successive transition phases. Let’s call these phases: motivate, facilitate, and reinforce. Deciding on the optimal behavior-change strategy will vary depending on which transition phase is being targeted. For example, to go from seeing no reason to change to having an intention to change, we need to feel motivated. To progress from having an intention to change to actually making a change, we need to feel capable. Finally, desired behaviors need to be reinforced to avoid relapsing into less favorable behavior patterns.
Applied behavioral insights
A recent review (Keller et al., 2019) provides insights on ways to stimulate movement through these behavioral stages. Experimental studies have successfully used phone-based conversation (Bamberg, 2013) or a mobile app (Sunio et al., 2018) to help participants reduce car use, and videos and textual information to help them limit beef consumption to weekly recommendations (Klöckner & Ofstad, 2017). Researchers followed participants over a period of 4 to 8 weeks and found that, as participants progressed along the stages, they enacted the desired behaviors more frequently.These are the strategies they used:
Motivate the desired behavior by discussing its health, environmental, and social benefits. For example, reducing car use helps protect the climate, and limiting beef to weekly recommendations helps protect against cardiovascular disease and certain types of cancer. In addition, highlighting that our peers are also taking steps toward the desired behavior can help increase motivation and perceived capability.
Facilitate the desired behaviorby helping participants make concrete how-to plans. We all face different barriers depending on our living situation and personal preferences. Getting to know these barriers allows us to provide alternatives suited to different lifestyles. For example, limiting beef consumption to weekly recommendations can be achieved by eating smaller portions of beef, by sometimes replacing beef with leaner meats, or by trying vegetarian meals. For transportation behavior, the use of technology can be particularly helpful to plan for daily commutes.
Reinforce the desired behavior by finding ways to overcome challenges. Implementation planning — in which the changer anticipates situational obstacles (e.g., will I be able to find vegetarian food on holiday?) and finds ways to proactively manage them — can help develop new desired habits (Gollwitzer & Sheeran, 2006). For example, a potential problem for households with young children is that, when trying to make a dietary change, the kids might not like the new recipes. Swapping recipes with other parents, and joining blogs where feedback and suggestions are shared, is one way to face this challenge ahead of time (Klöckner & Ofstad, 2017). Providing feedback can also help sustain motivation levels.
Consider the contextual hurdles
A lack of infrastructure, access to alternatives, or poor design can impede our capability to change our behavior. Nudging or choice architecture is one approach for getting rid of contextual barriers. For example, bike lanes can make cycling safer and reduce travel time. Going back to my own example, the city where I live is one of the best Canadian Cities for Biking, which played a key role in facilitating my behavior-change. Combined with easy access to bike parking, urban planning helps make cycling more convenient. Incentives and rebates could also be used to address other contextual barriers and incentivize change. All that’s left from there is to set a behavior-change course and ride.
Bamberg, S. (2013). Applying the stage model of self-regulated behavioral change in a car use reduction intervention. Journal of Environmental Psychology, 33, 68–75. https://doi.org/10.1016/j.jenvp.2012.10.001
Gollwitzer, P. M., & Sheeran, P. (2006). Implementation intentions and goal achievement: A meta‐analysis of effects and processes. In Advances in Experimental Social Psychology (Vol. 38, pp. 69–119). Academic Press. https://doi.org/10.1016/S0065-2601(06)38002-1
Keller, A., Eisen, C., & Hanss, D. (2019). Lessons learned from applications of the stage model of self-regulated behavioral change: A review. Frontiers in Psychology, 10. https://doi.org/10.3389/fpsyg.2019.01091
Klöckner, C. A., & Ofstad, S. P. (2017). Tailored information helps people progress towards reducing their beef consumption. Journal of Environmental Psychology, 50, 24–36. https://doi.org/10.1016/j.jenvp.2017.01.006
Sunio, V., Schmöcker, J.-D., & Kim, J. (2018). Understanding the stages and pathways of travel behavior change induced by technology-based intervention among university students. Transportation Research Part F: Traffic Psychology and Behavior, 59, 98–114
About the Author
Karine completed a PhD in the Environmental Psychology Lab at the University of Victoria. She received a Graduate Student Research Award from the Society for Environmental, Population, and Conservation Psychology (Div. 34) of the American Psychological Association for her work on developing a tool to measure psychological barriers to pro-environmental behavior. Her research focuses on applying behavioral science to tailor interventions to group-specific barriers and motivators. Her main interest lies in combining her experience working in government and academia to find effective solutions to behavioral challenges.