Delivering tailored smoking cessation support by SMS textmessage

Delivering tailored smoking cessation support by SMS textmessage Research team Stephen Sutton A Toby Prevost Hazel Gilbert James Jamison Sue Boase Melanie Sloan Susan Smith James Brimicombe Felix Naughton General Practice and Primary Care Research Unit University of Cambridge fmen 2@medschl. cam. ac. uk

What is tailoring? ¢ 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)

Mi. Quit development work 2005/6 Systematic review 2006/7 Interview study (qualitative) Intervention development Pre-test study (qualitative) 2007/8 2008 - 2010 MRC framework phase Phase 0 Phase 1 Theoretical and Intervention targets, evidence generation modelling and barriers Phase 2 Feasibility and acceptability

Acceptability and feasibility RCT - Mi. Quit Pregnant smokers were randomised to: ¢ Tailored support - Mi. Quit (n=102) • Tailored self-help leaflet • 12 week programme of tailored ‘push’ text-messages • • Instant support ‘pull’ text-message facility • • ¢ Tailored to 26 characteristics Target theory-based cognitive determinants of smoking behaviour Provide general support and encouragement 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)

Mi. Quit findings 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

Limitations of current system ¢ 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

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, Emotion. Sense, 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 Research team Stephen Sutton A Toby Prevost Hazel Gilbert James Jamison Sue Boase Melanie Sloan Susan Smith James Brimicombe Felix Naughton General Practice and Primary Care Research Unit University of Cambridge fmen 2@medschl. cam. ac. uk

Mi. Quit Motivational text ‘mm’ – sent day 12 Have you set a quit date yet Julie? Setting a date can help you to plan your quit & - High motivation to quit - Previously quit for over a month - Previous quit was difficult - Reason for quitting - Current smoking rate Although you found your longest previous quit hard work Julia, you managed to stay quit for over a month. You can do it again

Mi. Quit Motivational text ‘mm’ – sent day 12 Have you set a quit date yet Julie? Setting a date can help you to plan your quit & - 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 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