Title: Targeting multiple levels of ‘the smoking cessation system’ using novel scientific approaches
Funder: Cancer Research UK

Abstract: 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. AIMS This programme will develop and apply novel scientific approaches to increase the population rate of smoking cessation, targeting multiple levels by: i) integrating theory and data from population surveys and experimental studies in computational models; ii) optimising and evaluating wide-reach, hybrid human-digital-pharmacological interventions. The cross-cutting themes are: i) addressing inequalities using a mixed-methods approach, combining co-design and lived experience with epidemiology; ii) methodological innovation including use of ontologies and open-science principles; iii) transdisciplinary integration to identify risk profiles and accelerate development of emerging treatments. These aims were co-produced with a PPIE group. METHODS We will: 1. Substantially extend the Smoking Toolkit Study, our widely-used CRUK-funded, national, monthly series of household surveys of the English population with 12-month telephone follow-up, by adding 102,000 adults in 60 waves. This representative survey asks detailed questions on smoking and smoking cessation to provide population-level estimates of factors influencing quit attempts and success. We will apply general linear models and time-series analyses to understand the systems-level impact of: i) novel nicotine products on quitting activities; ii) the ongoing COVID-19 pandemic on smoking behaviour patterns; iii) novel tobacco control policies (e.g., increased age-of-sale). This research theme will be informed by, and refine, behaviour change theory and the development of a new agent-based model of smoking cessation. 2. Optimise hybrid human-digital-pharmacological smoking cessation interventions through our strategic collaboration with the developer of the world’s most popular cessation app (>5.5 million downloads). Priority projects: i) co-develop an embedded Just-In-Time-Adaptive-Intervention to prevent lapses identified from novel digital biomarkers using machine learning, and evaluating effectiveness in a large RCT; ii) use the app to conduct a large pragmatic trial comparing digital recommendation of the inexpensive pharmacotherapy, cytisine, with varenicline to establish whether cytisine can increase quit rates at scale with large population impact. HOW RESEARCH RESULTS WILL BE USED Close links with PPIE groups and UK tobacco control stakeholders provides the opportunity for the programme’s scientific advances to translate into policy to achieve the UK’s smoke-free target. Our findings, alongside the new computational model, will develop our theoretical understanding of the processes by which behavioural, pharmacological and digital support bring about smoking cessation, and behaviour change more broadly, to generate more effective interventions to reduce avoidable cancer deaths.


Research activity codes: 3.1 PRIMARY PREVENTION INTERVENTIONS TO MODIFY BEHAVIOURS OR PROMOTE WELL-BEING
Health categories: CANCER AND NEOPLASMS;CARDIOVASCULAR;RESPIRATORY;STROKE