The COVID-19 pandemic provided a stark reminder that societies will struggle to address global challenges unless they are able to change behaviour at scale. The widely adopted ‘nudge’ approach epitomizes an individualistic, deficit model of human cognition and motivation that leverages or overcomes people’s weaknesses and biases to get them to do things they would otherwise not. By contrast, we argue that tackling the challenges facing humanity requires a collective, capacity-building approach – one that boosts the competences, opportunities, and motivations of individuals to act together.

However, engaging people in research can sometimes become a source of re-traumatisation or activation for the people participating in the research. So being a trauma-informed content designer means not only focussing on the outcomes that designers produce, but also on the process that designers use to arrive at those outcomes. This means considering trauma-informed design research as the collective responsibility of anyone involved in making it happen, from design researchers to content designers and others.

This study aims to (1) identify and categorize the strategies used in digital health interventions over the past 25 years; (2) explore the differences and changes in these strategies across time periods, countries, populations, delivery methods, and senders; and (3) serve as a valuable reference for future researchers and practitioners to improve the effectiveness of digital health interventions.

It works like this. Over a short period of three recycling collections, households put their Not Sure Box out along with the usual containers, throwing in it anything they aren’t sure is recyclable. On collection day, council staff sort recyclable items into the recycling and leave feedback in the box about how to correctly dispose of remaining items.

What's new in COM-B 2.0? 1.‘Individual-level’ COM-B is distinguished from ‘Population-level’ COM-B2.COM-B components are more precisely defined and linked to the Behaviour Change Intervention Ontology (BCIO)3.COM-B components are broken down into key influences that can form the basis for a detailed diagnosis of what needs to change to influence a given behaviour in a given population and context.

At its core, the Power Walk is a new lens through which to see a neighborhood, guided by a series of prompts to reflect on what could change and where capacity exists to change it. It’s a way of understanding the possibilities that people see in the world around them, and discussing what collective power they have to realize those possibilities.

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. However, these results need to be interpreted with caution due to a potential publication bias. This new meta-analytic framework provides cognitive principles for organizing nudge and sludge with corresponding behavioural impacts.

This package includes everything you need to sell and run paid discovery sessions with your clients, including questionnaires, worksheets, guides, and more. 

wait this graph is crazy BART installed anti-fare-hopping gates and the amount of station maintenance and cleanup they had to do went to basically zero strong evidence that the poor condition of public transit is fairly easy to fix + caused by a very small group of people

What can behavioural scientists do differently when working on complex problems? Given the need for differentiated methods for different kinds of systems, and particular caution about existing approaches for complex and chaotic domains, applied behavioural scientists should be considering the appropriateness of the cornerstones of applied work, such as defining target behaviours. early on in strategic development, as shown in the table below. The Cynefin framework is a ‘sense-making’ framework – where sense-making is defined by the author David Snowden as “making sense of the world in order to act in it”. It distinguishes between 3 primary systems: ordered, complex, chaotic, which are defined by the type of constraints (or absence of constraints) in that system. Each type of system is described not just how it is constrained, but also describes how to best take action.

What can behavioural scientists do differently when working on complex problems? Given the need for differentiated methods for different kinds of systems, and particular caution about existing approaches for complex and chaotic domains, applied behavioural scientists should be considering the appropriateness of the cornerstones of applied work, such as defining target behaviours. early on in strategic development, as shown in the table below. The Cynefin framework is a ‘sense-making’ framework – where sense-making is defined by the author David Snowden as “making sense of the world in order to act in it”. It distinguishes between 3 primary systems: ordered, complex, chaotic, which are defined by the type of constraints (or absence of constraints) in that system. Each type of system is described not just how it is constrained, but also describes how to best take action.

Fundamentals of Inclusive Research Presenter(s): Cherish Boxall, Heidi Green, Frances Sherratt, Shaun Treweek decorative image to accompany text This guide provides four approaches to making research more inclusive. Groups of people, such as those from minoritised/racialised ethnicities, impaired capacity, and those experiencing socioeconomic disadvantage, generally experience poorer health outcomes than groups of people with more societal privilege. In parallel, these groups have been historically underserved in health research. This situation means that the findings of health research might not be transferable to the people who stand to benefit most, potentially allowing health inequalities to continue and most definitely not contributing to solving the problem of inequity. There are many historical and current reasons for under-representation in research. The most common reasons include a lack of trust and ease of access (e.g., small visit windows, cover for dependants). Although different groups might face unique barriers, this practical resource will provide a starting place to help research be more inclusive through a broad suite of approaches. The four pillars of the fundamentals of inclusive research are access, relevance, trust and recognition. > Download the workbook PDF with a check guide to get started on inclusive practice and community engagement.

obs-to-be-done is a great concept for innovators, helping to take the customer perspective and discovering customer insights for innovation and growth strategies. When applying JTBD in practice, however, innovators often get lost. The Job Hierarchy, developed by Vendbridgeand applied in dozens of JTBD projects, can help to maintain orientation and focus, and thereby to exploit the full potential of this powerful concept. Die Job Hierarchie As the word hierarchy implies, we use it to think JTBD in three different levels: The Bigger Why The Deeper Why The Lower How

Intervention Mapping is the most comprehensive approach to systematic behavior change (O'Cathain et al., 2019). For this reason, applying Intervention Mapping can been daunting. In this paper, I discuss the mistakes I made when applying the various iterative steps of Intervention Mapping in the design, implementation, and evaluation of an intervention aiming to reduce HIV stigma in health care settings in the Netherlands.

Personalized nudging (PeN) promises greater intervention effectiveness, especially for heterogenous populations. However, developments in PeN are hindered due to a lack of conceptual clarity and high methodological variability. We present a framework for PeN to tackle these challenges. We argue that personalization is contingent on personal data availability and choice environment malleability. Applying these factors to a nudge’s content, design, and underlying mechanism, we suggest that various levels of PeN exist, from simple name changes to more technologically sophisticated adaptive approaches. These levels highlight various novel methodological considerations, which we split into theory-driven (top down) and data-driven (bottom up) approaches. Finally, we discuss how our framework supports practitioner goals and reveals future research directions.

Creating a bot persona document. The part teams usually miss: Persona is the consistent personality users infer from your agent’s language choices — documented as constraints that guide every utterance. It prevents tone drift. It gives QA something testable. It makes “fun vs. professional” a decision, not a debate. And when persona isn’t defined, the agent becomes inconsistent in the places users notice most: greetings, errors, and handoffs.

To meet UK Net-Zero emissions targets, meat consumption must decrease. We present results from two studies evaluating interventions to reduce purchasing of meat-containing meals across university cafeterias in Oxford, UK. Study 1 tested whether two dynamic descriptive norm messages changed meal purchasing. Over eight weeks, four cafeterias displayed a norm message incorporating a socially ‘close’ referent group and three cafeterias displayed a message incorporating a socially ‘distant’ referent group. Two cafeterias were assigned a no-message control condition. A generalised linear mixed effect model suggested both messages decreased odds of cafeteria diners purchasing vegetarian meals, in comparison to control, 'Close' Message: Ratio of Odds Ratios (ORs)=0.79, 95% 95% CI [0.72, 0.86]; 'Remote' Message: Ratio of ORs=0.84, 95% CI [0.76,0.92]. Study 2 involved three pre-post experiments testing whether different interventions changed meal purchasing: re-positioning vegetarian products, increasing vegetarian availability, and introducing vegetarian defaults. Generalised linear models suggested each intervention was associated with significant increases in odds of diners purchasing vegetarian meals, Positioning: OR=1.33, 95% CI [1.24,1.44]; Availability: OR=1.60, 95% CI [1.45, 1.75]; Defaults: OR=1.77, 95% CI [1.61, 1.95]. These study results could be due to norm messaging being less effective at promoting vegetarian meals than interventions in availability, defaults, and positioning. But, given the study designs, they could instead be due to self-selection effects, or regression to the mean.

PCS yields three important discoveries in this investigation: First, context variables are more predictive of behavior for some individuals than others. Second, contrary to common wisdom, there is no “magic number” for how long it takes to form a habit. Instead, the speed of habit formation appears to vary significantly between behavioral domain: Gym habits take months to form and handwashing habits take weeks to form. Third, consistent with prior research on nonhuman animals, more habitual gymgoers are reward-insensitive, responding less to a well-designed behavioral intervention

Massive snowfalls like the one that hit the US east coast this week usually spell trouble for traffic. But critics of America's car-centric transport network are using the snow - and Twitter - to demonstrate how roads should be redesigned to make them safer for pedestrians.

This paper offers a refreshed and expanded view of how behavioural science can support sustainable development. It presents a comprehensive, evidence-based resource designed to help countries integrate behavioural insights into their policies and programmes for achieving the Sustainable Development Goals (SDGs). At the heart of the paper is a global database of 201 behavioural and nudge interventions, each aligned with one or more of the 17 SDGs. You can explore the full database here: https://docs.google.com/spreadsheets/d/1tWy0X2Aq08kIUNYG-Cw5FQsvakdKSyKGKen7_hc2F48/edit?gid=1627241714#gid=1627241714

A psychiatrist couldn’t keep up with the demand for mental health care. So he hired grandmothers. He asked himself a simple question: who do people already trust with their problems? The majority said it was grandmothers. They are wise, respected and embedded in the community. He trained them in basic therapy for common mental health disorders and gave them benches in public spaces. The results speak for themselves : → Thousands sought support → Depression symptoms dropped → A randomised trial showed it worked better than standard primary care

video: https://www.youtube.com/watch?v=yK3ElXX5S6E

The Cultural Currents Institute's proprietary SPREAD framework is ideal for testing and refining messages and strategies at the conceptual phase, diagnosing and troubleshooting campaigns that may be struggling after launch, and accelerating efforts that have already found some success. The core concepts of the framework are introduced here. Simple to Remember and Share Plausible to its Intended Audience Relatable to Common Lived Experience Emotional and Evocative Actionable With Clear Steps Duplicable With Low Effort and High Fidelity

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What works better is grouping the reasons someone struggles with a service, rather than segmenting the people who experience those struggles. This is the basis of the Universal Barriers to Access approach. Over time, the Government Digital Service received thousands of calls from people unable to use parts of its services. By analysing this data, we identified 11 common barriers—recurring patterns that explain why services fail for users, regardless of their background or situation.

Welcome to the Complex Systems Framework Collection, where you will find ways to consider the differences between simple, complicated, complex and chaotic. Whether you're a problem solver, leader, and/or learner, we hope you will find ideas here that resonate, challenge conventional wisdom, and push your thinking about complex problems in new directions.

Brian Cugelman

They collated 20 studies with 2,601 participants, studying the time it takes to turn new behaviours into automatic habits. ² The average time they reported? ➝ 106-154 days. With substantial variability, from 4-335 days. The time depended on factors like the: ↳ Type of habit ↳ Feelings about the habit ↳ Frequency performing the behaviour

drachten traffic experiment