1. The impact of biomarker feedback on smoking – evidence from a pilot study. Lion Shahab Cancer Research Health Behaviour Unit Department of Epidemiology & Public Health University College London lion.shahab@ucl.ac.uk

2. What are biomarkers & what’s the evidence? Biomarkers = Biological indices of harm (e.g. lung function test), exposure (e.g. CO levels) or genetic susceptibility (e.g. CYP2D6) Increase in quit attempts when using biomarkers in comparison to standard interventions (McClure, 2001) Bovet et al, 2002: –Scan of carotid artery during routine examination –Evidence of plaque, shown to smokers –17.6 vs 6.5 % quit-rates at 6 months follow-up Background

3. How could harm biomarker feedback work? Fear Appeal  Individualised harm biomarkers counteract optimistic bias  Quitting stops further development of plaque (Wiggers et al, 2003)  Work on fear appeals suggests that imagery is particularly effective (Keller&Block, 1996) – less likely to be filtered by conscious critical apparatus (Horowitz, 1970) PERCEIVED EFFICACY (Self-Efficacy, Response Efficacy) PERCEIVED THREAT (Susceptibility, Severity) FEAR Individual Differences No threat perceived > No response Protection Motivation Defensive Motivation Message Acceptance Message Rejection Danger Control Process Fear Control Process BEHAVIOUR CHANGE NO BEHAVIOUR Change = = Extended Parallel Process Model; Witte, 1998 Background

4. How could harm biomarker feedback work? Emotional Processing Cognitive vs. emotional processing –Cognitive / intellectual appraisal of information > cognitive processing –Emotive / intuitive appraisal of information > emotional processing Smokers process information cognitively but not emotionally correct Emotional processing model > fear network (Foa & Kozak, 1986) Access to fear network to change emotional response, e.g. exposure therapy (arachibutyrophobia) –Individualised, visual material more effective in evocating of fear structures (Vrana et al.,1986; Burnkrant & Unnava, 1995) Background

5. Looked at cardiovascular (CVD) outpatients to implement intervention because: –Would particularly benefit from cessation –Easy to do as carotid artery scan part of routine CVD outpatient files scrutinised to identify current smokers CVD outpatients who were smokers were sent invitation to participate in study 1 week prior to clinic appointment at Guy’s Hospital London On day of appointment, outpatients were asked to participate if they were: –Regular smokers –Literate in English Rationale & Recruitment Methodology

6. Procedure Methodology

7. Intervention Normal Carotid Artery Abnormal Carotid Artery

8. Intervention Normal Carotid Artery Abnormal Carotid Artery

9. Questionnaires assessed demographic variables (T1), cognitive outcomes (T2) and behavioural outcomes (T3) Methodology Procedure

10. Measures T1: Demographic variables (before intervention) –Age, Gender, Education, Nicotine Dependence, Readiness to quit T2: Cognitive outcomes (immediately after intervention) –Intention to stop smoking, perceived threat (susceptibility and severity), perceived efficacy (self-efficacy, response efficacy) and worry –Two 7-point response scales for each item, e.g.: T3: Behavioural outcomes (4 weeks after intervention) –Smoking status & smoking cessation behaviours – predicts transition from smoker to non-smoker (France, Glasgow & Marcus 2001) E.g. talking to GP/Nurse about quitting; ringing quit smoking helpline; using NRT/Zyban; attempting to quit; setting quit date How likely do you think you are to develop smoking related diseases? (Susceptibility 1) Please circle one number Very unlikely1234567 Very likely Methodology

11. Participant Characteristics Shahab, Hall & Marteau, in press Results

12. Main Outcomes Shahab, Hall & Marteau, in press # assessed 4 weeks after scan Results

13. Fear and danger control: the case of self-efficacy Shahab, Hall & Marteau, in press ^ Median split scale * * p<0.05 Perceived threat= response No perceived threat= no response Results

14. Fear and danger control: the case of self-efficacy Shahab, Hall & Marteau, in press ^ Median split scale * * p<0.05 Message rejection Message acceptance Results

15. Emotional processing: the case of worry The more worried about CVD, the more likely smokers were to have attempted to quit 815 ** ** p<0.01 YesNo Worry predicted both cessation attempts and the number of smoking cessation behaviours after controlling for age, gender, nicotine dependence and educational level Quit Attempt Results

16. Current study Intervention was cost and time-effective and easy to implement (5 mins of clinicians time) Intervention acceptable to patients As predicted intervention increased perceived threat of smoking related diseases and engagement in smoking cessation behaviours Tentative conclusions

17. Current study Provides preliminary evidence for the importance of emotional processing in changing health behaviours Highlights role of self-efficacy in smoking cessation interventions Biomarker feedback may create opportune moment during which smokers more amenable to quit advice or referral to specialist services Tentative conclusions

18. Study limitations Hospital sample > can’t generalise to normal population and sample size too small to make definite statements Longer follow-up period needed Objectively verified smoking status (e.g. cotinine) Better measure of emotional processing (e.g. GSR) Tentative conclusions

19. Thanks to: Prof Marteau and Dr Hall at King’s College Mr Taylor and Dr Padayachee at Guy’s Hospital MRC