Demonstration Projects

Demo Project 1 aimed to understand the perceived misalignment between the behavioural and social science advice that was provided to the UK Government and the COVID-19-related policy decisions that were subsequently implemented, including how advice was communicated, received and acted upon and what barriers/enablers influencing the communication and use of advice were given.

This project aimed to expand on research showing that communicating evidence on policy effectiveness can increase policy support via belief updating. It aimed to assess the effect that exposure to evidence about policy effectiveness (statistical and anecdotal) has on beliefs about policy effectiveness and the differential effect of exposure to congruent and incongruent combined evidence. It also assessed what evidence evaluation processes people engage in when exposed to combined evidence about policy effectiveness and the effect these processes have on beliefs in policy effectiveness and support for these policies.

Ontologies are ways of representing information that promotes clarity, consistency, and coherence. They are used in science to facilitate search, inference, and interoperability across data sets and academic disciplines. To maximise ontologies for use within the behavioural sciences, three things need to be achieved: first, ontologies in a domain should be interoperable to be used together. However, behavioural scientists do not currently have a method - or ‘workflow’ - for making ontologies interoperable. The DEMO-INTER project developed and evaluated a method for achieving interoperability between ontologies. Second, ontologies should be used to make working with datasets easier (e.g., searchable) and interoperable so that they can be combined to maintain coherence and provide insights that would not have been possible for data sets used in isolation. The DEMO-DATA project developed and applied a methodology for annotating data sets in behavioural and social sciences, using data sets used for modelling population trends in smoking and e-cigarette use as an example. Third, to advance theory development, evaluation and use, it is important to develop a consistent, coherent and comprehensive way of representing theory constructs. The DEMO-THEORY project mapped constructs in theories of behaviour change onto ontology classes for the purposes of theory searching, comparison and integration.

View DP3's OSF pages to read the protocols for the DEMO-INTER, DEMO-DATA and DEMO-THEORY sub projects. 

Tackling climate change requires a substantial long-term shift in people's lifestyles related to consumption domains such as energy, transport, and food, which drive carbon emissions and present opportunities for policy intervention to facilitate reduction. However, making well-informed decisions on what policy intervention will be effective and feasible to implement in a given context is difficult. While countries often seek best-practice examples of environmental policies from abroad, gauging the public's acceptance of these policies in their own context is challenging. Estimating the transferability of environmental attitudes and behaviours across socio-demographic groups and its impact on policy support could enhance learning from international comparisons. Current approaches, such as multi-level regression models, may yield biased results when the number of countries is limited. An alternative method involves developing data-driven personas—rich archetypal segments of the target population—to aid policymakers in envisioning how end-users might respond to policies. In collaboration with the OECD, this project leveraged recent advances in data-driven persona development to assess the transferability of public support for various environmental policies across socio-demographic clusters and countries. The study used the 2022 OECD Environmental Policy and Household Behaviour (EPIC) survey (OECD, 2023) with over 17,000 respondents in nine countries.

Given speeding's significant impact on collision and injury outcomes and the complexity of its causes, there's a pressing need to evaluate effective behavioural interventions for reducing driver speeds. Previous reviews highlight gaps in current interventions, particularly overlooking key influences such as beliefs about safety and external motivators like time pressures. This project aimed to update evidence on the most influential motivational and capability influences of speeding behaviour and assess the efficacy of interventions. We reviewed behavioural interventions, including using the Behaviour Change Intervention Ontology (BCIO) to code the interventions found, conduct a pilot study of the most promising of these, and then ran an observational study and intervention on public roads.