There were some significant differences between BCTs reported in implementation and de-implementation interventions suggesting that researchers may have implicit theories about different BCTs required for de-implementation and implementation. These findings do not imply that the BCTs identified as targeting implementation or de-implementation are effective, rather simply that they were more frequently used. These findings require replication for a wider range of clinical behaviours. The continued accumulation of additional knowledge and evidence into whether implementation and de-implementation is different will serve to better inform researchers and, subsequently, improve methods for intervention design.
Costing is the process of data collection and analysis for estimating the cost of a health intervention. High-quality cost data on SBC are critical not only for developing budgets, planning, and assessing program proposals, but can also feed into advocacy, program prioritization, and agenda setting. To better serve these data needs, these guidelines aim to increase the quantity and quality of SBC costing information. By encouraging cost analysts to use a standardized approach based on widely accepted methodological principles, we expect the SBC Costing Guidelines to result in well-designed studies that measure cost at the outset, to allow assessment of cost-effectiveness and benefit-cost ratios1 for SBC programming. Such analyses could also potentially help advocates for SBC to better make the case for greater investment in SBC programming.2 These guidelines lay out a consistent set of methodological principles that reflect best practice and that can underpin any SBC costing effort.
Psychological reactance theory (PRT; Brehm, 1966) posits that when something threatens or eliminates people’s freedom of behavior, they experience psychological reactance, a motivational state that drives freedom restoration. Complementing recent, discipline-specific reviews (e.g., Quick, Shen, & Dillard, 2013; Steindl, Jonas, Sittenthaler, Traut-Mattausch, & Greenberg, 2015), the current analysis integrates PRT research across fields in which it has flourished: social psychology and clinical psychology, as well as communication research.
BehaviourWorks Australia and the Victorian Government Behavioural Insights Unit have developed an evidence-informed toolkit to help behavioural insights researchers and practitioners to start with scale up in mind, including how to: Learn about scale up, its challenges, and useful frameworks. Identify which behaviour to target with an intervention. Assess the feasibility of different intervention ideas. Select a scalable behaviour change intervention. Design or adapt an intervention for testing and scale up. Test scale up assumptions about your intervention in a pilot or trial. This website provides videos and tutorials on how to use the toolkit, and extra resources to help achieve behavioural impact at scale. All content will be iterated upon; we welcome feedback and the opportunity to develop better tools.
Our project tracks behavioural science evidence and advice about COVID-19 vaccine uptake. The handbook is for journalists, doctors, nurses, policy makers, researchers, teachers, students, parents – in short, it’s for everyone who wants to know more: about the COVID-19 vaccines, how to talk to others about them, how to challenge misinformation about the vaccines. The handbook is self-contained but additionally provides access to a Wiki of more detailed information, found here: https://sks.to/c19vax.
Before we dive in, here is a quick summary of the proposed taxonomy of behaviour change failures: No effect Backfiring Intervention is effective but it's offset by a negative side effect Intervention isn't effective but there's a positive side effect A proxy measure changes but not the ultimate target behaviour Successful treatment effect offset by later (bad) behaviour Environment doesn't support the desired behaviour change Intervention triggers counteracting forces
Five principles for an effective COVID-19 lexicon 1. Messaging never merely provides factual information – communication unavoidably conveys many assumptions (the subtext, indirect meanings, inferences, and implications). 2. Messaging should be lexically and grammatically precise and thus easy to enact and adhere to. 3. Messaging should be ‘irony-resistant’. 4. ‘Branding’ or sloganeering should not come at the expense of clarity and precision. 5. Messaging should be underpinned by evidence about what is effective.
SHIFT is an acronym for five psychological factors that make consumers more inclined to engage in pro-environmental behaviours: social influence, habit formation, individual self, feelings and cognition, and tangibility.
The behavioural change enterprise disproportionately focuses on promoting successes at the expense of examining the failures of behavioural change interventions. We review the literature across different fields through a causal explanatory approach to identify structural relations that impede (or promote) the success of interventions. Based on this analysis we present a taxonomy of failures of behavioural change that catalogues different types of failures and backfiring effects. Our analyses and classification offer guidance for practitioners and researchers alike, and provide critical insights for establishing a more robust foundation for evidence-based policy. Behavioural change techniques are currently used by many global organisations and public institutions. The amassing evidence base is used to answer practical and scientific questions regarding what cognitive, affective, and environment factors lead to successful behavioural change in the laboratory and in the field. In this piece we show that there is also value to examining interventions that inadvertently fail in achieving their desired behavioural change (e.g., backfiring effects). We identify the underlying causal pathways that characterise different types of failure, and show how a taxonomy of causal interactions that result in failure exposes new insights that can advance theory and practice.
Again: you don’t convince people. People convince themselves. Studies done as far back as the 1940’s by Kurt Lewin showed that lectures about why people should change their behavior were effective a measly 3% of the time. But when people self-generated reasons for the same activity, behavior change occurred 37% of the time. People reject ideas they are given and act on ideas they feel they came up with themselves.
Includes “periodic table“ of behavior change techniques
Thammasat Design Center
summary of key points of book
Welcome to The Behavioural Insights Team’s Barrier Identification Tool. What is it: This tool will help you to identify and categorise the barriers to a behaviour that you’re trying to change. Step 1: The COM-B Model Overview - a behaviour change framework that can be used to identify barriers to behaviour. Step 2: Review a worked example of how this tool can be used to identify barriers to a behaviour. Step 3: Use the tool to identify barriers to a behaviour you’re trying to change.
We fall off track because a part of us isn’t sure that the goal we’re working toward is going to make our lives better. This causes inner conflict, and when there’s inner conflict, we do the easiest thing of all: nothing. I’ve presented this simple worksheet to many clients, and I’ve found that it helps determine what’s really holding them back.
In particular, a focus on habits is useful when: The most effective approaches depend more on patiently persisting over long periods of time, rather than overcoming brief, but intense, obstacles. The behavior you want can eventually run in the background of your life, not requiring lots of deliberate thinking and effort. You’re looking to make long-term changes to your routine or lifestyle, rather than a temporary shift for particular circumstances. Understanding the limitations of habits is part of what makes them powerful. If you go in with the right expectations, you’ll be far more likely to make them stick.
The evidence shows that this kind of behaviour change needs to happen collectively, not just individually. So we need joined-up governance at local, national and international levels. Food systems also contribute significantly to greenhouse gas emissions. This can be addressed by reducing waste or directing it back into the supply chain. A mix of different measures will be most effective. The evidence shows that taxation is one of the most effective ways to modify behaviour. Accreditation and labelling schemes can also have an impact.
To become a better catalyst for change, Berger suggests to: Find the gaps. Rather than push or persuade someone, highlight a gap between their attitudes and their actions, and then get them to persuade themselves. For example: If someone is reluctant to wear a mask at work, ask them if they would wear one if their child or elderly parent were in the office. Ask why that same care or concern isn't present with their colleagues? Provide a “menu” of choices. Rather than unilaterally force a single solution on others, give people the freedom and autonomy to choose from a few options. This is one way to reduce people’s gut resistance, and again, help them persuade themselves. Cut through perceived risks. If people feel like a new idea is controversial or risky, explain your personal experience as to why you think it is more relatable and less extreme than they think.
case study of anti-smoking program for kids that backfired
not really a lit review, but covers key behavior change concepts and how they can be applied to covid
The Patient Activation Measure is a valid, highly reliable, unidimensional, probabilistic Guttman‐like scale that reflects a developmental model of activation. Activation appears to involve four stages: (1) believing the patient role is important, (2) having the confidence and knowledge necessary to take action, (3) actually taking action to maintain and improve one's health, and (4) staying the course even under stress. The measure has good psychometric properties indicating that it can be used at the individual patient level to tailor intervention and assess changes. (https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1475-6773.2004.00269.x)