Here, we develop a novel cognitive framework by organizing these interventions along six cognitive processes: attention, perception, memory, effort, intrinsic motivation and extrinsic motivation. In addition, we conduct a meta-analysis of field experiments (i.e. randomized controlled trials) that contained real behavioural measures (n = 184 papers, k = 184 observations, N = 2 245 373 participants) from 2008 to 2021 to examine the effect size of these interventions targeting each cognitive process. Our findings demonstrate that interventions changing effort are more effective than interventions changing intrinsic motivation, and nudge and sludge interventions had similar effect sizes.

The new toolkit crosses local, central and international government action. It has many of the elements of the previous framework but also covers new ground. The most obvious is that we have changed the horizontal axis to better reflect the way government works in practice. This has meant including a number of new areas namely, influencing, engaging, designing, developing, resourcing, delivering and controlling (or managing). The vertical axis still follows the same logic from ‘softer’ more collaborative power at the top, down to more formal government power at the bottom of the axis. The update includes many familiar things from nudging behaviour to convening power and also adds new areas like deliberative approaches such as citizen juries. This is the framework for Policy Lab's new Government as a System toolkit. The new Government as a System toolkit framework. When looking across the whole system, it now has 56 distinct actions. Of course this isn’t an exhaustive set of options, you could create more and more detail as there is always more complexity and nuance that can be found in government. Importantly, we want policymakers to be considering how multiple levers are used together to address complex problems.

In the first in his series of columns Ogilvy UK's head of strategy argues that accommodating behaviour - rather than adapting it - might be key to its change

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization.

Free Behavior Design, Innovation and Change Tools These frameworks started out as internal tools we would use on client projects at Aim For Behavior, that would help us save time and create better outcomes for the customers and the companies we were working with. We are always adding more frameworks or iterating the current ones based on the feedback.

“We tested the effectiveness of different messages aimed at addressing climate change and created a tool that can be deployed by both lawmakers and practitioners to generate support for climate policy or to encourage action,” says Madalina Vlasceanu, an assistant professor in New York University’s Department of Psychology and the paper’s lead author. The tool, which the researchers describe as a “Climate Intervention Webapp,” takes into account an array of targeted audiences in the studied countries, ranging from nationality and political ideology to age, gender, education, and income level. “To maximize their impact, policymakers and advocates can assess which messaging is most promising for their publics,” adds paper author Kimberly Doell, a senior scientist at the University of Vienna who led the project with Vlasceanu. Article: https://osf.io/preprints/psyarxiv/cr5at Tool: https://climate-interventions.shinyapps.io/climate-interventions/

From a process perspective, our task then becomes figuring out the optimal behavioral flow that reduces the friction between intentions and desired behaviors and stimulates progression through the journey – assuming at least a moderate interest in what is being offered by the organization.

The Behaviour Change Strategy Matrix means you can approach behaviour change methodically. Assess the complexity of the desired behaviour change and the target group's readiness in order to select a behaviour change strategy. So that you can design solutions that truly resonate with your target group's abilities and willingness to change.

This article reviews 10 techniques used to identify opinion leaders to promote behavior change. Opinion leaders can act as gatekeepers for interventions, help change social norms, and accelerate behavior change. Few studies document the manner in which opinion leaders are identified, recruited, and trained to promote health. The authors categorize close to 200 studies that have studied or used opinion leaders to promote behavior change into 10 different methods. They present the advantages and disadvantages of the 10 opinion leader identification methods and provide sample instruments for each. Factors that might influence programs to select one or another method are then discussed, and the article closes with a discussion of combining and comparing methods.

The world's largest collection of resources and data on behavioral science.

Miro whiteboard based on BCTTv1 - 93 BCTs

Hi, I'm Robert I hope this concept card is useful for you and helps you add a new tool to your toolbox. As someone who helps teams develop products, services and experiences, I did not see many open resources out there that combine behavioral science with other strategy and design processes, so I decided to take my experience and create frameworks and boards to share for free. If you have questions on the framework you can connect with me on Linkedin or see my website.

A unique compendium of the latest behavioural insights, distilled, applied and combined to strengthen your ideas

When it comes to reducing obesity, evidence shows that changing food environments is more effective than measures that try to educate or change the behaviour of individuals. The interventions that participants consider to be most acceptable are the same as those that they perceived to be most effective at tackling obesity. However, the interventions that were reported to be least effective and least acceptable — such as reducing portion sizes and the taxation of unhealthy foods — may actually have the greatest potential for promoting healthy eating at the population level. While we must be cautious with how we interpret correlations like this, it suggests that addressing the disconnect between the evidence base and public understanding may be a viable way of influencing public acceptability

We present four strategies, informed by behavioural science, that government and researchers can deploy to improve the use of evidence in policy decisions.

Developed over several years, the BehaviourWorks Method is a tried and tested approach to changing behaviours. Consisting of three primary phases - Exploration, Deep Dive and Application - The Method can be used in full, or in parts, to gather evidence on the behaviour change approach that is most likely to work.

Behavior Audit - user journey Miro board

BC patterns are a collection of reoccurring solutions used in Behavioural Design to change people’s behaviour. They are patterns that designers, change makers and problem solvers can consider when solving people problems and designing behaviour change.

TRA has added a layer of thinking to the well-established habit loop – can we think beyond push notifications for cues and think beyond a discount as a reward? We analysed five different habit models and over 60 case studies in order to understand the breadth and depth of cues and rewards. Our framework takes these learnings and provides a thorough checklist for the cue, the behaviour and reward for strengthening habits. When you’re working on strengthening a one-time behaviour into a routine habit, consider the various options for each stage.

Mutually-Assured Non-Complacency (MANC) Introducing MANC, a system that helps you achieve your goals. Plainly, MANC is a system that uses the people closest to you to assure that you don’t fall into status quo ruts. It’s Mutually-Assured Non-Complacency. How does it work? First, you define the new desired personal behavior (a.k.a. your goal). Then, you put in a system to achieve it (a.k.a. accountability system). This system gives your friends and family a role in your success. So you think you can MANC? The worksheet gives you the recipe. The videos give you the motivation to start today.

Growing open-sourced database of different commitment devices to help you stick with your intentions and achieve your long-term goals. Read this article for more information on Commitment Devices and how to make the most of this database.

A quick reference guide to creating behavioral maps and behavioral blueprints

Bonus talks Why You Forget Everything And What to Do About It w/ Bec Weeks – https://youtu.be/VoDlOmHbaWE The Sneaky Things That Keep Good Habits From Sticking w/ Jessica Malone – https://youtu.be/oCwMXY7u73A Nicolas Fieulaine from NFÉtudes – https://youtu.be/E-XNZUGvVT0 ––– Timestamps 0:00 Event Intro 6:53 The Science of Habit Change with David Neal 38:10 The Science of Mindfulness with Dr. Clare Purvis 53:03 Creatures of Context with David Perrott 1:21:05 Time Smart: How to Reclaim Your Time and Live a Happier Life with Ashley Whillans 2:05:36 The Invisibility of Habit with Wendy Wood 2:34:19 Digital Behavior Change in Health with Jennifer La Guardia & Aline Holzwarth 2:59:11 Better Decision Making at Work: 5 Core Heuristics (& How to Manage Them) with Scott Young, BVA Nudge Unit 3:22:32 All the small things - How behavioral science can help you unlock success in love and at work with Logan Ury & Liz Fosslien 4:09:53 How to apply behavioral insights to cyber security training with Harriet Rowthron from BestAtDigital 4:22:44 Making Meaning When Life Stinks with Yael Schonbrun 4:54:47 The Power of Identity with Dominic Packer 5:30:40 The Untapped Science of Less with Leidy Klotz 5:55:10 Day Wrap-Up with Samuel Salzer & Peter Judodihardjo

This toolkit has been designed by the Research and Evaluation Unit (RIMU) at Auckland Council to be useful to those wishing to improve public programmes or services, policy development, or team decision-making. It draws on a range of existing resources produced by the Behavioural Insights Team, the OECD and others (see ‘other resources’ on the next page). This toolkit has two components that can be used either separately or together. The first component is a step-by-step process for developing a behavioural intervention. It guides the user through understanding existing behaviours, identifying a desired behaviour, brainstorming ideas for promoting the desired behaviour, and robustly testing the best ideas. The user should follow the steps in the order they are numbered. It is focused on key questions to ask at each step. It is not a complete guide to how to answer these questions, however, and the user may need to rely on other research and evaluation resources to help with each step. The second component of the toolkit is a series of ‘brainstorming’ cards. The cards cover many important behavioural principles to keep in mind when looking to improve programmes, policies, or decision-making. Each card includes a description of the behavioural principle, some examples, and suggestions for how to apply the principle. They can be used on their own or to brainstorm ideas as in the step-by-step process above. To help with navigation, the card set has been organised into a series for better services and a series for better decisionmaking, although there is overlap in the use of the cards. The former is marked with a red dot in the top left corner and the latter with a green dot.

In this chapter we explore three approaches to ensuring that an effective intervention does lead to impact: they are scaling, dissemination, and knowledge translation. Each pathway can increase your impact - i.e., desired behaviour and societal change - but approach this goal from different directions and with emphasis on different activities and outputs. We will introduce you to the three approaches before deep diving into when and how to apply each approach.

On the whole, however, these behavioral interventions have been somewhat underwhelming, exposing an inherent brittleness that comes from three common “errors of projection” in current behavioral design methodology: projected stability, which insufficiently plans for the fact that interventions often function within inherently unstable systems; projected persistence, which neglects to account for changes in those system conditions over time; and projected value, which assumes that definitions of success are universally shared across contexts. Borrowing from strategic design and futures thinking, a new proposed strategic foresight model—behavioral planning—can help practitioners better address these system-level, anticipatory, and contextual weaknesses by more systematically identifying potential forces that may impact behavioral interventions before they have been implemented. Behavioral planning will help designers more effectively elicit signals indicating the emergence of forces that may deform behavioral interventions in emergent COVID-19 contexts, and promote “roughly right” directional solutions at earlier stages in solution development to better address system shifts.

Method:Three participatory workshops were held with the independent Welsh residential decarbonisation advisory group(‘the Advisory Group’)to (1)maprelationships betweenactors, behavioursand influences onbehaviourwithin thehome retrofitsystem,(2)provide training in the Behaviour Change Wheel framework(3)use these to developpolicy recommendationsfor interventions. Recommendations were analysed usingthe COM-B (capability, opportunity, motivation) model of behaviourtoassesswhether they addressed these factors. Results:Twobehavioural systems mapswere produced,representing privately rented and owner-occupied housing tenures. The main causal pathways and feedback loops in each map are described.

In 2010, Colombia's defense minister contacted an ad agency to create an idea to demobilize FARC members, the oldest guerrilla army in Latin America. The agency, after spending over a year talking to nearly 100 of its members, learned two main things (1). -First, guerrilla members are ordinary men and women and not only guerrillas, a fact which is often forgotten after 60 years at war. -Secondly, they are more likely to demobilize during Christmas as it is a sensitive and emotional period. Based on these insights, they had a clever idea to put a Christmas tree in strategic walking paths in the middle of the jungle that would light up when someone passed by with a message promoting demobilization. The results? Three hundred thirty-one people who demobilized named this idea as one of the reasons to do so. Over the years, several campaigns from the same agency were quite successful, and overall, they were named in over 800 demobilizations. Causality, of course, cannot be established. Nevertheless, any measurable, non-violent efforts like this one are praised. Next time you think you have a difficult-to-reach customer, maybe think again!

CUBES (to Change behavior, Understand Barriers, Enablers, and Stages of change) is a comprehensive framework for analyzing behavior developed by Surgo Ventures. As described in the video with Peter Smittenaar below, CUBES builds on evidence-based behavioral models that are widely used across sectors and includes drivers that show evidence of changing behavior. It illustrates how adopting a new behavior is a process of stages; at each stage, people are influenced by internal and environmental factors (see Figure 1). The CUBES framework articulates three critical components of behavior change: The path toward a target behavior comprises distinct stages of change, progressing from knowledge to intention, action, repetition, and finally, habit. Perceptual and contextual drivers can act as enablers or barriers that influence each individual, shaping their progression through each stage of change. Influencers in the form of family and friends, community, and society can affect these drivers, either directly or via media channels.

A pressing goal in global development and other sectors is often to understand what drives people’s behaviors, and how to influence them. Yet designing behavior change interventions is often an unsystematic process, hobbled by insufficient understanding of contextual and perceptual behavioral drivers and a narrow focus on limited research methods to assess them. We propose a toolkit (CUBES) of two solutions to help programs arrive at more effective interventions. First, we introduce a novel framework of behavior, which is a practical tool for programs to structure potential drivers and match corresponding interventions. This evidence-based framework was developed through extensive cross-sectoral literature research and refined through application in large-scale global development programs. Second, we propose a set of descriptive, experimental, and simulation approaches that can enhance and expand the methods commonly used in global development. Since not all methods are equally suited to capture the different types of drivers of behavior, we present a decision aid for method selection. We recommend that existing commonly used methods, such as observations and surveys, use CUBES as a scaffold and incorporate validated measures of specific types of drivers in order to comprehensively test all the potential components of a target behavior. We also recommend under-used methods from sectors such as market research, experimental psychology, and decision science, which programs can use to extend their toolkit and test the importance and impact of key enablers and barriers. The CUBES toolkit enables programs across sectors to streamline the process of conceptualizing, designing, and optimizing interventions, and ultimately to change behaviors and achieve targeted outcomes.