Targeting multiple levels of 'the smoking cessation system' using novel scientific approaches
This programme will develop and apply novel scientific approaches to increase the population rate of smoking cessation.
Background
Tobacco smoking causes 20% of cancers worldwide. The UK will not achieve the Government's target of being 'smoke-free' by 2030 on the current trajectory, particularly in disadvantaged groups.
Introduction
This programme, led by University College London (UCL), is developing and applying novel scientific approaches to increase the population rate of smoking cessation, targeting multiple levels by:
- integrating theory and data from population surveys and experimental studies in computational models
- optimising and evaluating wide-reach, hybrid human-digital-pharmacological interventions
The University of Sheffield is principally involved in the first of these aims. We are developing a novel agent-based model (ABM) of smoking cessation and using this model to understand how novel nicotine products (e.g. e-cigarettes) are affecting smoking rates and to estimate the impact of new policy action in this space.
Agent-based modelling
Our scientific approach is informed by the overarching 'COM-B' model of behaviour change, developed by our collaborators at UCL. The model represents how behaviour (e.g. making a quit attempt) is influenced by a person's capabilities, opportunities and motivations in relation to that behaviour, and how those factors are influenced by the wider social context.
Developing the behavioural science of smoking cessation requires integrating the insights from overarching theories and empirical data into empirically realistic computational models of behaviours in real-world contexts.
The Sheffield team will build on existing work to develop a new agent-based model of smoking cessation, informed by the COM-B model and parameterised by research on our unique population-based and digital datasets. Our application of the model will generate and prioritise novel approaches for systems-level interventions and evaluations to support the 2030 smoke-free target.
Team
The project is led by Professor Jamie Brown and Professor Lion Shahab at University College London with a team at the University of Sheffield, led by Professor Robin Purshouse, developing the agent-based models.
Key project information
This project is funded by Cancer Research UK.
Dates
April 2022 – March 2027
Funding
£531,098
Principal investigators
Professor Jamie Brown (UCL)
Professor Lion Shahab (UCL)
Professor Robin Purshouse (Sheffield)
Institutions involved
University of Sheffield
University College London
Key contact
You might also be interested in…
SPECTRUM
The SPECTRUM Consortium is a multi-university, multi-agency research consortium focused on the commercial determinants of health and health inequalities, funded by the UK Prevention Research Partnership.
Robin Purshouse speaks at the University of Exeter
Professor Robin Purshouse recently gave a talk on Building agent-based models using computational intelligence as part of the University of Exeter's Computer Science Seminar Series.
SARG study on UK alcohol tax reforms published in The Lancet Public Health
A new study published this week in The Lancet Public Health by the Sheffield Addictions Research Group shows that while recent reforms to UK alcohol taxation are a step in the right direction, they are unlikely to significantly improve public health outcomes without further changes.