delivering tailored smoking cessation support by sms text- message felix naughton general practice...

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

fmen2@medschl.cam.ac.ukfmen2@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

fmen2@medschl.cam.ac.ukfmen2@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