how-to guide - excellent explanation
Life course changes disrupt old habits and may create a mood for more change. • An intervention to promote sustainable behaviours was tested among 800 households. • Behaviour change was more likely if participants recently had moved house. • The results were compared with non-movers and a no-intervention control group. • The ‘window of opportunity’ lasted up to three months after relocation.
Sunstein and Thaler used the example of a high school cafeteria layout to demonstrate how small changes in our environment can influence our behavior, and we’ve discussed how a well-laid out office space can improve program participation rates. The example and our observations inspired MDRC’s Center for Behavioral Science (CABS) to create an interactive training session on the power of physical space to provide nudges. We asked training participants — staff at workforce development programs that help people find and keep employment — to try organizing their space with different goals in mind by designing a hypothetical high school cafeteria. Workshop participants received paper cut-out icons for all the essential materials — salads, hot food, snacks, desserts, beverages, cash registers, tables — and were asked to organize a logical cafeteria environment. But the directions had a catch. Each group received a unique goal: arrange the materials to maximize either: Healthy eating, Profits, or Efficiency.
You can either have rapid uptake OR large-scale adoption, but generally you don't find both together in these types of initiatives.
Want to learn more about applying behavioural insights to public policy? Take our free online course—Behavioural insights for public policy. There’s six learning modules, each with a quiz, to measure learning and understanding. It should help you understand the basics of BI, the mission and work of BETA, as well as the ethical application of the field. It takes about two hours – but you can save your progress and do it at your own pace.
there is no clear consensus on how long it takes to form a habit is because this has nothing to do with the behavior pattern itself and everything to do with the underlying coherence of the values dictating that behavior.
Extension of System 1/System 2 thinking model from a social ecological perspective - Systems 1-5
This is the website for a PhD-level mini-course in behavioral public economics developed by Hunt Allcott and Dmitry Taubinsky. Through the lens of neoclassical economics, the role of government is to provide public goods, correct externalities, provide information, and address other market failures. In practice, however, some public policies are motivated by the concern that people do not act in their own best interest. For example, many countries ban drugs, tax cigarettes, alcohol, and sugary drinks, or subsidize retirement savings and energy-efficient appliances, all largely on the grounds that consumers would be better off consuming more or less than they do. Standard approaches to policy analysis rely on revealed preference assumptions to measure an agent’s welfare. Under these assumptions, the direct effect of any policy that changes choices is to reduce consumer welfare. However, empirical evidence from behavioral economics in a variety of domains suggests that people sometimes do make systematic mistakes. The field of behavioral public economics extends the theoretical and empirical tools of public economics to incorporate the possibility of consumer mistakes into questions about policy evaluation and design. This is a PhD-level mini-course in behavioral public economics. In this course, we’ll consider questions like the following: How can we do welfare analysis if choice does not necessarily identify utility? How do we empirically measure consumer biases? How do we set socially optimal policies in settings when consumers may not act in their own best interest? Nudges change behavior at low cost. Does that mean they are a good idea? What are the costs and benefits of tax complexity?
soap-infused sticks of chalk
Well, if we want to sway other people to our “correct“ vision of things, we are most likely to do that by having a strong relationship with them. Ironically, it is through carefully and compassionately listening to others that we are more likely to sway their views.
Great examples of how behavioral insights have been applied to behavior change in India
2 excellent case studies
Nearly every major challenge the United States faces—from alleviating unemployment to protecting itself from terrorism—requires understanding the causes and consequences of people’s behavior. Even societal challenges that at first glance appear to be issues only of medicine or engineering or computer science have social and behavioral components. Having a fundamental understanding of how people and societies behave, why they respond the way they do, what they find important, what they believe or value, and what and how they think about others is critical for the country’s well-being in today’s shrinking global world. The diverse disciplines of the social, behavioral, and economic (SBE) sciences ―anthropology, archaeology, demography, economics, geography, linguistics, neuroscience, political science, psychology, sociology, and statistics―all produce fundamental knowledge, methods, and tools that provide a greater understanding of people and how they live.
Discarding classical solutions such as information campaigns, it offers a much simpler alternative: make the healthy options more tempting. How? By changing their names. Several research teams in the US have tried this strategy in various school canteens and they found that making the names “seductive”, catchy or funny can induce children to eat healthier.
In this paper, we discussed multiple ways how behavior change interventions can backfire. We provided a framework to help facilitate the discussion of this topic, and created tools to aid academics in the study of this realm, and support practitioners to remain mindful of the potential risks.
Directing drivers to “think of themselves” successfully led to far more drivers switching off their idling engines: More drivers switched off their engines in the private self-focused condition (51%) compared with the baseline condition (20%). “The odds ratios revealed that drivers were 1.83 times more likely to switch off their engines in the instructive watching eyes condition, and 4.82 times more likely in the private self-focus condition than in the baseline condition,” Meleady and colleagues write.
When the growth team took a step back, they realized it wasn’t enough to trigger just any notification. They needed to “show the right things to users at the right time — creating ‘aha moments’” where the user experienced the product’s core value. Rather than indiscriminately bombard the user with notifications, they concluded that they needed to be “really thoughtful about which messages to send which users” and focus “more of [their] resources on engaging users that were likely to churn.” Taking a page from Facebook, here are 5 kinds of engagement messages that work to activate, retain, and grow customers. Highly personal and targeted, these emails show off your product’s core value, ferry your users to their “aha moments”, and get people engaging with your product and brand again and again.
Behavioral Design Teams: A Model for Integrating Behavioral Design in City Government - open source playbook
The doors will soon open at Saskatchewan's first children's hospital, but some psychiatrists say the building is rife with safety and suicide risks.
Two examples of campaigns tackling misbeliefs - one addressing misperceptions of the likelihood of an event (girls contracting HIV in South Africa) and one addressing misperceptions of social norms (women working outside the home in Saudi Arabia):
In this randomized clinical trial of 602 overweight and obese adults from 40 states across the United States, gamification interventions with support, collaboration, and competition significantly increased physical activity compared with the control group during the 24-week intervention. The competition arm had the greatest increase in physical activity from baseline during the intervention; during the 12-week follow-up, physical activity was lower in all arms, but remained significantly greater in the competition arm than in the control arm.