The impact of COVID-19 related regulations and restrictions on mobility and potential for sustained climate mitigation across the Netherlands, Sweden and the UK: a data-based commentary

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Abstract

Human behaviour change is necessary to meet targets set by the Paris Agreement to mitigate climate change. Restrictions and regulations put in place globally to mitigate the spread of COVID-19 during 2020 have had a substantial impact on everyday life, including many carbon-intensive behaviours such as transportation. Changes to transportation behaviour may reduce carbon emissions. Behaviour change theory can offer perspective on the drivers and influences of behaviour and shape recommendations for how policy-makers can capitalise on any observed behaviour changes that may mitigate climate change. For this commentary, we aimed to describe changes in data relating to transportation behaviours concerning working from home during the COVID-19 pandemic across the Netherlands, Sweden and the UK. We display these identified changes in a concept map, suggesting links between the changes in behaviour and levels of carbon emissions. We consider these changes in relation to a comprehensive and easy to understand model of behaviour, the Opportunity, Motivation Behaviour (COM-B) model, to understand the capabilities, opportunities and behaviours related to the observed behaviour changes and potential policy to mitigate climate change. There is now an opportunity for policy-makers to increase the likelihood of maintaining pro-environmental behaviour changes by providing opportunities, improving capabilities and maintaining motivation for these behaviours.

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The behaviour change wheel: A new method for characterising and designing behaviour change interventions

Susan Michie, Maartje M. van Stralen, Robert H. West (2012)

Background Improving the design and implementation of evidence-based practice depends on successful behaviour change interventions. This requires an appropriate method for characterising interventions and linking them to an analysis of the targeted behaviour. There exists a plethora of frameworks of behaviour change interventions, but it is not clear how well they serve this purpose. This paper evaluates these frameworks, and develops and evaluates a new framework aimed at overcoming their limitations. Methods A systematic search of electronic databases and consultation with behaviour change experts were used to identify frameworks of behaviour change interventions. These were evaluated according to three criteria: comprehensiveness, coherence, and a clear link to an overarching model of behaviour. A new framework was developed to meet these criteria. The reliability with which it could be applied was examined in two domains of behaviour change: tobacco control and obesity. Results Nineteen frameworks were identified covering nine intervention functions and seven policy categories that could enable those interventions. None of the frameworks reviewed covered the full range of intervention functions or policies, and only a minority met the criteria of coherence or linkage to a model of behaviour. At the centre of a proposed new framework is a 'behaviour system' involving three essential conditions: capability, opportunity, and motivation (what we term the 'COM-B system'). This forms the hub of a 'behaviour change wheel' (BCW) around which are positioned the nine intervention functions aimed at addressing deficits in one or more of these conditions; around this are placed seven categories of policy that could enable those interventions to occur. The BCW was used reliably to characterise interventions within the English Department of Health's 2010 tobacco control strategy and the National Institute of Health and Clinical Excellence's guidance on reducing obesity. Conclusions Interventions and policies to change behaviour can be usefully characterised by means of a BCW comprising: a 'behaviour system' at the hub, encircled by intervention functions and then by policy categories. Research is needed to establish how far the BCW can lead to more efficient design of effective interventions.

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The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions.

Susan Michie, Michelle Richardson, Marie Johnston … (2014)

CONSORT guidelines call for precise reporting of behavior change interventions: we need rigorous methods of characterizing active content of interventions with precision and specificity. The objective of this study is to develop an extensive, consensually agreed hierarchically structured taxonomy of techniques [behavior change techniques (BCTs)] used in behavior change interventions. In a Delphi-type exercise, 14 experts rated labels and definitions of 124 BCTs from six published classification systems. Another 18 experts grouped BCTs according to similarity of active ingredients in an open-sort task. Inter-rater agreement amongst six researchers coding 85 intervention descriptions by BCTs was assessed. This resulted in 93 BCTs clustered into 16 groups. Of the 26 BCTs occurring at least five times, 23 had adjusted kappas of 0.60 or above. "BCT taxonomy v1," an extensive taxonomy of 93 consensually agreed, distinct BCTs, offers a step change as a method for specifying interventions, but we anticipate further development and evaluation based on international, interdisciplinary consensus.

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Dilemmas in a general theory of planning

Horst Rittel, Melvin M. Webber (1973)

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Author and article information

Journal

Journal ID (nlm-ta): UCL Open Environ

Journal ID (publisher-id): UCLOE

Title: UCL Open Environment

Abbreviated Title: UCL Open Environ

Publisher: UCL Press (UK )

ISSN (Electronic): 2632-0886

Publication date (Electronic, pub): 24 February 2022

Publication date (Electronic, collection): 2022

Volume: 4

Electronic Location Identifier: e032

Affiliations

[1 ]Centre for Behaviour Change, Department of Clinical, Educational & Health Psychology, University College London, London, UK

[2 ]Department of Psychology, University of Bath, Bath, UK

[3 ]Stockholm Environment Institute, Stockholm, Sweden

[4 ]Research Group Psychology for Sustainable Cities, Amsterdam Research Institute for Societal Innovation, Amsterdam University of Applied Sciences, Amsterdam, The Netherlands

[5 ]Department of Psychology, Faculty of Behavioural and Social Sciences, University of Groningen, Groningen, The Netherlands

[6 ]Department of Computer and Information Science, Linköping University, Linköping, Sweden

[7 ]Centre for Climate Change and Social Transformations (CAST), Linköping, Sweden

Author notes

*Corresponding author: E-mail: e.corker@ 123456ucl.ac.uk

Author information

Elizabeth Corker https://orcid.org/0000-0002-2055-7493

Kaloyan Mitev https://orcid.org/0000-0001-6148-4852

Astrid Nilsson Lewis https://orcid.org/0000-0002-2090-4379

Thijs Bouman https://orcid.org/0000-0001-7940-892X

Stefan Holmlid https://orcid.org/0000-0002-2529-4303

Fiona Lambe https://orcid.org/0000-0003-3664-9891

Susan Michie https://orcid.org/0000-0003-0063-6378

Matthew Osborne https://orcid.org/0000-0003-0272-1496

Reint Jan Renes https://orcid.org/0000-0003-2448-9480

Linda Steg https://orcid.org/0000-0002-8375-9607

Lorraine Whitmarsh https://orcid.org/0000-0002-9054-1040

Article

DOI: 10.14324/111.444/ucloe.000032

PMC ID: 10208342

SO-VID: 0b731b8b-547e-48c0-8ba3-e19d3f4c842f

License:

This is an open access article distributed under the terms of the Creative Commons Attribution Licence (CC BY) 4.0, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.