1. Robert West University College London November 2015
Applying behavioural science to the development of digital aids to smoking cessation
Robert West
University College London
November 2015

2. Digital behaviour change interventions
Are good for
Dynamic tailoring
Providing immediate reward
Displaying images
Social networking
Monitoring and feedback
Data gathering
Data sharing
Cumulative development

3. The development process

4. Activity map Context Concept Knowledge Goals Opportunities Development
Testing
Constraints
Activity map
Context
Stakeholders
Implementation
Abandonment
Collaborators
West R, Michie S (2015) Developing and Evaluating Digital Behaviour Change Interventions. In Preparation.
Risks
Promotion

5. Knowledge

6. COM-B model of behaviour change
Michie S, M van Stralen, West R (2011) The behaviour change wheel: A new method for characterising and designing behaviour change interventions. Implementation Science, 6, 42..

7. Top level framework for understanding behaviour change interventions
Intervention/ comparator
Mechanism of action
Behaviour change
Usage metrics
Context
Intervention-behaviour complex
Effect
West R, Michie S (2015) Developing and Evaluating Digital Behaviour Change Interventions. In Preparation.
denotes ‘Influences’

8. Mechanisms of action

10. For smoking cessation the focus is momentary motivation to smoke and not to smoke

13. West R (2009). The multiple facets of cigarette addiction and what they mean for encouraging and helping smokers to stop. COPD: The Journal of Chronic Obstructive Disease, 6,

14. Intervention components

15. Focus on behaviour change techniques that can be delivered by smartphones and have evidence of effectiveness when delivered by other modalities

16. Promote effective medication use
Increase uptake and engagement, manage expectations
Enhance coping
Promote relaxation, provide distraction, increase self-control, promote mindfulness
Enable avoidance or escape
Negotiate strategies, train behaviour, provide triggers
Provide reward for not smoking
Congratulate, provide incentives, increase enjoyment and satisfaction
Boost resolve not to smoke
Build confidence, provide social support, boost morale, maintain commitment
Boost concern about smoking
Create disincentives, create negative imagery, increase salience of harms

17. Examples from team at UCL

18. StopAdvisor
Website designed to aid cessation in smokers across the social spectrum
Found in a large RCT to be effective in lower income smokers; currently being developed further by Public Health England
Brown J, Michie S, Geraghty A, Yardley L, Gardner B, Shahab L, Stapleton J, West R, (2014) Internet-based intervention for smoking cessation (StopAdvisor) in people with low and high socioeconomic status: a randomised controlled trial. Lancet Respiratory Medicine, 12,

19. SF28
Sets goal of managing 28 days smoke-free and provides advice and tools to achieve this
Promising results from an uncontrolled observational study; usage data being studied
Ubhi HK, Michie S, Kotz D, Wong WC, West R, (2015). A mobile app to aid smoking cessation: Preliminary evaluation of SmokeFree28. Journal of Medical Internet Research, (17)1:e17

20. SmokeFree
Most popular smoking cessation app available with 3000 new users per day, developed by Dave Crane
RCT of earlier version being written up; currently studying usage patterns

21. BupaQuit
Smoking cessation app based on SF28 with added craving management tools
Currently undergoing RCT to evaluate usage patterns and effectiveness of the craving management components

22. SmokeFree Baby
Smoking cessation and reduction app for pregnant smokers, aims to maximise number of smoke-free days
Currently being evaluated in a ‘factorial’ experiment to optimise content

23. NRT2Quit Smoking cessation app developed to promote effective NRT use
Currently being evaluated in an RCT

24. Challenges

25. Building
Competing with 100s of other applications
Maintaining engagement
Keeping up with an ever-changing user environment
Adapting to changes in platforms and operating systems
Evaluating
Attracting enough users into evaluations
Collecting robust outcome data
Choosing or building the right comparator in evaluations

26. Conclusions

27. Research has yielded a robust model of the processes leading to lapse and relapse
Digital interventions could be well-equipped to target those processes to help smokers to stop
This includes components aimed at promoting effective medication use
There are 100s of digital interventions on the market but most do not deliver behaviour change techniques that would be expected to be effective
Research is just beginning to build and evaluate effective interventions based on behavioural science
There are major challenges to this but some promising results are emerging

28. Questions?