Delivering tailored smoking cessation support by SMS text-
message
Felix NaughtonFelix NaughtonGeneral Practice and Primary Care Research UnitGeneral Practice and Primary Care Research Unit
University of CambridgeUniversity of Cambridge
[email protected]@medschl.cam.ac.uk
School for Primary Care Research
Research teamResearch teamStephen SuttonA Toby PrevostHazel GilbertJames JamisonSue BoaseMelanie SloanSusan SmithJames Brimicombe
Computer-tailoring – use of a computer program to individualise feedback according to user characteristics
Increasing the personal relevance of feedback increases attention, use/consumption and adoption of message
Petty & Cacioppo (1986); Skinner et al (1999); Sutton et al (2007)
What is tailoring?
MiQuit development work
2005/6
2006/7
2007/8
2008 - 2010
MRC framework phase
Phase 0 Phase 1 Phase 2
Theoretical and Intervention targets, Feasibility andevidence generation modelling and barriers acceptability
Interview study (qualitative)
Pre-test study (qualitative)
Systematic review
Intervention development
MiQuit development work
2005/6
2006/7
2007/8
2008 - 2010
MRC framework phase
Phase 0 Phase 1 Phase 2
Theoretical and Intervention targets, Feasibility andevidence generation modelling and barriers acceptability
Interview study (qualitative)
Pre-test study (qualitative)
Systematic review
Intervention development
Acceptability and feasibility RCT - MiQuit
Pregnant smokers were randomised to: Tailored support - MiQuit (n=102)
• Tailored self-help leaflet• 12 week programme of tailored ‘push’ text-messages
• Tailored to 26 characteristics• Target theory-based cognitive determinants of smoking behaviour• Provide general support and encouragement
• Instant support ‘pull’ text-message facility• HELP – if they are struggling not to smoke• SLIP – if they have smoked and regretted it
Control group – non-tailored self-help leaflet (n=105)
Feasibility 94% of treatment participants received both intervention components 57% of sample on average replied to assessment text-messages 9% requested an instant support text-messages (mean messages requested = 1.3)
Acceptability 24% of treatment participants felt text-messages were annoying to some degree 9% opted to discontinue text-messages (but mostly for reasons other than annoyance)
Effectiveness estimate Cotinine validated abstinence at 3-months follow-up: treatment 12.5%, control 7.8%, (OR
= 1.68, 95% CI 0.66 – 4.31) Increased self-efficacy, harm beliefs and determination to quit in treatment arm
Naughton et al – in preparation
MiQuit findings
Text-messaging/mobile phones can deliver tailored support in real-time but currently not using real-time data
User initiated support is rarely used and not done so strategically
Limitations of current system
Using mobile sensing to tailor behavioural support
Passive
Proximity support triggers (GPS, Wi-fi etc.)• User/system specified high-risk locations e.g. friends house, pub, work
• Interaction with time of day, situation, behaviour change progress
Situation/state triggers (audio, EmotionSense, physiological etc.)• Specific situations e.g. with others, alone, moving
• Detection of emotional states related to relapse risk e.g. anger
Active Tailoring user initiated support according to situation/location
Future work
Could also help researchers and users learn about triggers of relapse
Tailoring behavioural support using mobile sensing would work well for other behaviours e.g. physical activity
Key points Need to establish acceptability of tailoring support to real-time
information Important that interventions are systematically developed and
evaluated
Thank you
Felix NaughtonFelix NaughtonGeneral Practice and Primary Care Research UnitGeneral Practice and Primary Care Research Unit
University of CambridgeUniversity of Cambridge
[email protected]@medschl.cam.ac.uk
School for Primary Care Research
Research teamResearch teamStephen SuttonA Toby PrevostHazel GilbertJames JamisonSue BoaseMelanie SloanSusan SmithJames Brimicombe
Have you set a quit date yet Julie? Setting a date can help you to plan your quit &
Although you found your longest previous quit hard work Julia, you managed to stay quit for over a month. You can do it again
- High motivation to quit
- Previously quit for over a month
- Previous quit was difficult
- Reason for quitting
- Current smoking rate
Motivational text ‘mm’ – sent day 12
MiQuit
Have you set a quit date yet Julie? Setting a date can help you to plan your quit &
If you are feeling low on motivation Julia, remind yourself how much money you will save by quitting - A rate of 5-a-day equals £40 a month and £500 a year
- Low motivation to quit
- Previously quit for less than a month
- Difficulty of previous quit
- Reason for quitting = money
- Current smoking rate 4-5 a day
Motivational text ‘mm’ – sent day 12
MiQuit