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Delivering tailored smoking cessation support by SMS text-message

Research team from University of Cambridge developed MiQuit, a tailored smoking cessation program delivered via text messages. The intervention includes personalized messages, real-time support, and self-help resources to help smokers quit successfully. Findings revealed high acceptability and feasibility, with increased abstinence rates and self-efficacy in the treatment group. Future work includes using mobile sensing for tailored behavioral support in real-time.

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Delivering tailored smoking cessation support by SMS text-message

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  1. Delivering tailored smoking cessation support by SMS text-message 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 fmen2@medschl.cam.ac.uk

  2. 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)

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

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

  5. 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)

  6. MiQuit 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

  7. 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

  8. 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

  9. 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

  10. 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 fmen2@medschl.cam.ac.uk

  11. 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 MiQuit Motivational text ‘mm’ – sent day 12 • High motivation to quit • Previously quit for over a month • Previous quit was difficult • Reason for quitting • Current smoking rate

  12. 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 MiQuit Motivational text ‘mm’ – sent day 12 • 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

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