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Hazel Gilbert Research Department of Primary Care and Population Health UCL Medical School

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Can we involve smokers who are unmotivated to quit in quitting activity?. Hazel Gilbert Research Department of Primary Care and Population Health UCL Medical School. Overview. Principles of tailoring Escape study Baseline characteristics and follow-up assessment. Self-help Materials.

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Can we involve smokers who are unmotivated to quit in quitting activity?

Hazel Gilbert

Research Department of Primary Care and Population Health

UCL Medical School



  • Principles of tailoring
  • Escape study
  • Baseline characteristics and follow-up assessment

Self-help Materials

  • Generic leaflets and manuals
  • Personalised generic
  • Targeted materials to particular groups
  • Individually Tailored Feedback
  • Definition: ‘intended to reach one specific person, based on characteristics unique to that person, related to the outcome of interest, and derived from an individual assessment’
  • (Kreuter et al 1999)

Individually Tailored Feedback

Personally relevant information:

  • greater attention
  • central route processing (deeper processing)
  • greater cognitive and behavioural change (Elaboration Likelihood Model. Petty and Cacioppo, 1981)

Evidence of effectiveness

‘evidence of the effectiveness of tailoring health behaviour change messages’ (Noar, Benac and Harris 2007) (meta-analysis of 57 studies)

‘material tailored for the individualincreases quit rates over and above standard materials and untailored materials’(Lancaster and Stead 2005) 17 trials (OR 1.42)


Phases of development

1) Understand determinants of the behaviour

Tailoring process ideally informed by established models of behaviour change

  • 2) Develop a framework of intervention objectives
    • motivation and readiness to quit
    • reason for quitting
    • dependence and self-image
    • cognitive expectations of the outcomes of quitting
    • perceived self-efficacy
    • offer skills and strategies to cope
    • social environment
    • encourage finding support

3) Develop tailoring assessment

  • Design questionnaire to assess the relevant individual characteristics
  • 4) Create the content of the feedback
    • Compose a message for each possible answer
  • 5) Design template
  • Style and Format
    • Font
    • Graphics
    • Colour
    • Tone
    • Reading and comprehension level


Individual assessment

Computer system


Message library of persuasive texts

Decision rules

Individualised output

Dijkstra 2008






Applications of Tailored Feedback in Primary Care

Eofcomputer-tailoredSmokingCessationAdvicein PrimarycarE

A Randomised Controlled Trial



To examine the effect of computer generated individually tailored feedback reports designed to help and encourage smokers to quit, on quit rates and quitting activity, when sent to smokers with varying levels of motivation and reading ability, identified from GP lists


NHS Smoking Cessation Service

  • Clinical approach:
  • Intensive face-to-face
  • Relatively high quit rates
  • Low participation rates
  • Unrepresentative
  • 3-6% of smokers use the services per year
  • Challenge for Primary Care services:
  • to reach the smokers who do not use clinics

Proactive recruitment

  • Contact individuals directly offering a service
  • Higher participation
  • More demographically representative
  • Can target specific population groups
    • Smokers not motivated to quit
    • Areas of high deprivation where smoking prevalence is higher

123 general practices recruited from the MRC GPRF

  • Practices identified current cigarette smokers (18 to 65) from patient records using the computer system
  • Random sample of 500 screened by GP, and sent Smoking Behaviour Questionnaire (SBQ), together with a covering letter from GP (n=60,000)
  • Smokers willing to take part returned the SBQ to research team at UCL
  • Randomised to Intervention or Control Group
  • Intervention Group
  • Standard NHS booklet
  • Computer-tailored feedback report adapted to reading level and readiness to quit
  • Additional assessment and feedback report one month after baseline

Control Group

Standard NHS booklet

6-month follow-up: postal questionnaire to assess smoking status, cognitive change, perception of the feedback, economic issues


Baseline characteristics



Response rate=11.75%




Respondents by readiness to quit

Of those planning to quit within the next 30 days (n=890): 339 (38.1%) set a quit date

Of those not planning to quit within the next 6 months (n=3203):

too difficult - 45.3% / want to smoke - 44.8% / both - 4.3%


Follow-up Assessment Response

Intervention Group only (N=3404)

4 weeks post baseline

Sent follow-up assessment + reminder=3350(98.4%)

Returns: Before reminder 968 (28.9%)

After reminder 817 (24.4%)

Total 1785 (53.3%)

Participants planning quit in 30 days less likely to return the follow-up assessment (p=0.012)


Follow-up Assessment Outcome

2= 197.48, p<.0001


Length of abstinence by readiness

Respondents not smoking 4 weeks post baseline (n=180)


Quit attempts by readiness

Respondents still smoking 4 weeks post baseline (n=1601)

2=235.698, p<.00001



  • The Escape trial has met recruitment targets in terms of motivation
  • By reaching smokers with no plans to quit in the near future, we are able to provide them with information that they would not otherwise receive or seek out
  • By completing the Smoking Behaviour Questionnaire, these smokers are engaging in reflection about their smoking behaviour
  • Might prompt them to consider changes to their lifestyle and behaviour
  • Quitting activity?

Tailored feedback + Proactive Recruitment

behavioural intervention principles of the clinical approach

participation rates of public health campaigns

provide personal, individually tailored self-help reports for a large population of smokers







Irwin Nazareth, Richard Morris

Department of Primary Care and Population Sciences, UCL

Stephen Sutton

Institute of Public Health, University of Cambridge


Christine Godfrey

Department of Health Sciences, University of York

Trial Co-ordinator

Camille Alexis-Garsee