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Keywords:

  • Brief interventions;
  • computer tailoring;
  • literacy;
  • primary care;
  • reading level;
  • self-help;
  • smoking cessation

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Aims

To evaluate the effectiveness of tailored cessation advice reports, including levels of reading ability, compared with a generic self-help booklet.

Design

Participants were randomised to receive standard non-tailored information or to receive standard information plus a cessation advice report and a progress report, both tailored to individual characteristics.

Setting

One hundred and twenty-three general practices located throughout the UK.

Participants

Questionnaires were mailed to 58 660 current cigarette smokers aged 18–65 years, identified from general practitioner records. Of the 6911 (11.8%) who completed the questionnaire, provided consent and were enrolled into the study, 6697 (11.4%) were included in the analysis.

Measurements

Follow-up was by postal questionnaire sent six months after randomisation, or by telephone interview for participants failing to return the questionnaire. The primary outcome was self-reported prolonged abstinence for at least three months at the six-month follow-up.

Findings

Quit rates on the primary outcome were not significantly different (3.2% versus 2.7%) (OR = 1.20, 95% CI [0.94, 1.54], P = 0.15). A significantly higher proportion of intervention group participants made a quit attempt during the follow-up period (32.3% versus 29.6%; OR = 1.13, 95% CI [1.01, 1.26], P = 0.026).

Conclusion

ESCAPE, a brief tailored smoking cessation intervention delivered by post and designed to reach a wide population of smokers, appears to increase the rate at which smokers try to stop, but if there is an effect on prolonged abstinence it is small.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Smoking is a major public health problem and the leading preventable cause of premature death; 23% of all UK deaths in middle age are attributed to smoking [1]. Despite this 22% of the population in the UK still smoke [2]. Although clinical specialist services offering individual face-to-face support are provided nationwide by the National Health Service (NHS), only around 5% of smokers use them [3, 4]. There is an urgent need to develop self-help interventions that will reach a wider range of smokers who are not able or willing to engage with intensive clinical services.

Traditional self-help materials can be offered to any smoker, but are limited by generic information that does not meet the needs of a diverse population of smokers [5]. Computer-based systems, however, can generate highly tailored advice reports, which apply the basic principles of behavioural interventions used in clinical practice [6], but can be inexpensively produced and delivered on a larger scale, with the potential to reach most smokers. Previous trials have produced mixed results, but, overall, demonstrate a small, but useful, effect of individually tailored self-help materials on smoking cessation [7].

Tailored self-help materials can address other important issues that can lead to suboptimal quit rates. Written advice, often written at a level beyond the literacy skills of many smokers [8], should be tailored to take account of the education and reading level of the individual. Additionally, with approximately 60–70% of smokers having no serious intentions to attempt to quit in the next year [9-11], further tailoring of messages to match and try to enhance the level of the smoker's motivation to quit is essential. Multiple mailings of tailored advice has also been shown to be more effective than a single mailing in promoting cognitive change in smokers with low readiness to quit [12], and stored data can be used at a later date in combination with new information provided by the smoker to update subsequent advice reports. We applied these principles to adapt an existing computer-based system, originally developed to generate individually tailored advice reports as an adjunct to telephone counselling [13], and developed a stand-alone brief intervention for use in primary care. We identified smokers from general practitioner (GP) lists, and recruited them proactively [14] to a randomised controlled trial designed to evaluate the effect of adding advice reports, tailored to relevant participant characteristics, including motivation to quit and levels of reading ability, to a generic self-help booklet, on smoking abstinence for at least three months assessed six months later.

Method

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Recruitment

General practices from the MRC General Practice Research Framework (n = 607) were approached, and 123 (20.2%) agreed to participate in the trial. Practices approached were selected to be representative geographically and in terms of socio-economic level [14]. All current cigarette smokers aged 18–65 years were identified using the computer system in participating practices. A random selection of 520–550 smokers (or all identified smokers in smaller practices) was then screened by the GP who excluded people they considered unsuitable for the project (i.e. people with severe mental impairment, or those who were severely or terminally ill). An invitation to participate in the trial was then sent by the GP to the remaining sample with a 10-page Smoking Behaviour Questionnaire (SBQ), formatted as an A5 booklet. Participants were told that they would be sent some information about quitting, and could be randomly selected to receive additional information based on their answers in the questionnaire. Non-responders were sent a reminder with a duplicate questionnaire between five and eight weeks later. Recruitment occurred between August 2007 and December 2008. Practice and participant characteristics are reported in more detail elsewhere [15, 16].

Randomisation and masking

Eligible smokers returning the completed questionnaire and signed consent form were assigned randomly to the control group or to the intervention group, according to an externally constructed randomisation plan (http://www.randomization.com) using block randomisation: blocks of eight (within which the order of assignment was random) within each practice. These blocked randomisation codes were generated externally and given to an independent administrator in sealed envelopes upon receipt of completed questionnaires. Participants were accepted into the study before knowledge of the next assignment in the sequence in order to minimise selection bias. Each study participant randomised received the treatment corresponding to the next free study number in the randomised sequence.

Interventions

  • 1
    Participants allocated to the control group received standard, non-tailored information (the NHS ‘Stop Smoking Start Living’ booklet) [17].
  • 2
    Participants allocated to the intervention group received the standard non-tailored information plus a computer-tailored advice report based on the information obtained in the baseline assessment questionnaire (SBQ), accompanied by a letter from the GP endorsing the information contained in the report. The SBQ assessed demographic characteristics (including educational level and normal daily reading), intention and motivation to quit, dependence, previous quit attempts, perceived advantages and disadvantages of quitting, self-efficacy and social environment. This information was used to generate the tailored reports which referred to relevant sections in the NHS booklet, and other relevant NHS booklets were also included (e.g. if they had children or worried about weight). Participants were sent a follow-up assessment one month after baseline, giving them the opportunity to be re-assessed in terms of current smoking status and readiness to quit, and receive a tailored progress report generated from this additional data.

All participants were mailed the relevant materials, according to their group allocation, within a few days of receipt of the completed baseline questionnaire.

(See Supporting Information for details of the development of the tailored advice report with examples.)

Outcome assessment

All participants were sent a postal questionnaire 6 months after randomisation. Participants failing to respond after two weeks were sent a reminder with a duplicate questionnaire, and all those failing to respond after a further two weeks were contacted by telephone to prompt them to return the questionnaire. At this point telephone interviewers also asked the participants two questions which constituted the basic outcome. All those failing to return the postal questionnaire after a further two weeks were contacted a second time by telephone to request a telephone interview. To avoid bias in outcome assessment, telephone interviewers were blinded to the allocation of the respondent.

This process meant that the collection of follow-up data was done over a five-month period from six months after baseline. Two participants who returned questionnaires more than 11 months (335 days) after the baseline questionnaire were treated as lost to follow-up.

Outcome measures

The primary outcome measure was self-reported prolonged abstinence for at least three months at the six-month follow-up, defined as answering ‘not at all’ to the question ‘How often do you now smoke cigarettes or roll ups?’ and ‘longer than 3 months ago’ to the question ‘When did you last smoke a cigarette?’ These responses were validated by answering ‘no’ to the question ‘Have you smoked cigarettes at all in the last 7 days even as little as a puff?’ This internal validity check allowed testing the consistency of the answers.

Participants who answered ‘not at all’ to the question ‘(How often) do you now smoke cigarettes or roll ups?’ but did not answer the question ‘When did you last smoke a cigarette’ were treated as missing data and assumed to be non-quitters (see Supporting Information).

Those answering the basic outcome questions only (Do you smoke cigarettes now? and When did you last smoke a cigarette?) had to report having smoked their last cigarette longer than three months ago in order to be classified as abstinent.

We did not use biochemical validation as it is not considered to be appropriate in trials such as this [18] which involve no face-to-face contact and a low intensity intervention. Moreover, minimal differences have been reported between self-report and validated quit rates in large scale population studies.

Secondary outcomes included self-reported prolonged abstinence for at least 1 month, using the same validity check as 3 months prolonged abstinence, point-prevalent abstinence of 7 days, defined as no smoking in 7 days, not even a puff, and 24 hour point-prevalent abstinence. We also collected self-report data on quit attempts and length of quit attempts in non-quitters.

Sample size and statistical analysis

The estimated effect size in the Cochrane review of individually tailored materials for smoking cessation was 1.42 (95% CI 1.26–1.61) [7]. We assumed a 3-month abstinence rate in a control group receiving standard materials to be at the upper limit of estimates of spontaneous long term abstinence in the population (i.e. 3%) and 4.2% in the intervention group (assuming an OR of 1.42). Thus, the target sample size of 7250 was chosen to carry out the trial with the resources available [19] to give the minimum power required (77%) to detect a difference of this size, assuming a two-tailed test and alpha of 0.05. Actual recruitment (6697 participants) was slightly lower than estimated, reducing power to 74%.

All analyses were conducted on an intention-to-treat basis. Participants with a missing outcome were assumed to be smokers at follow-up, and were assumed to have not made a quit attempt. Logistic regressions were used to compare binary outcomes between the intervention and control groups, both unadjusted and adjusted for baseline characteristics (gender, age, deprivation score, dependence score, intention to quit, determination to quit, previous quit attempts and living with other smokers). An individual deprivation score ranging between 0 and 5 was computed by adding one point for each of the following: renting their home; no car; no educational qualifications; manual occupation; and being unemployed or a full-time student [20]. Missing adjustment variables were imputed by multiple imputation by chained equations (ice command in Stata [21]), including all baseline characteristics in the model. To address the multi-centre effect resulting from the observations sampled from different practices, we used the sandwich estimator of the standard error, relaxing the assumption of independently distributed observations.

Quit attempts, length of the attempt, and change from baseline in the number of cigarettes per day were compared between conditions in the subgroup of participants who reported smoking at follow-up, using χ2-tests and t-tests. We sought evidence for a possible difference in intervention effect according to the reading level of the participants, which was an a priori hypothesis. In order to investigate the sensitivity of the findings to the missing data assumptions, the analysis was also performed assuming that participants with missing data had the same quit rate as participants with complete data in the same group. In addition, the analysis was performed with a wider range of assumptions, ranging from a scenario where non-responders in the intervention group had similar quit rates to responders, while those in the control group had nil success, to the opposite scenario.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Response

Questionnaires were mailed to 58 660 patients (mean per practice = 477). After discarding questionnaires returned from people who were ineligible, either because they were not cigarette smokers (n = 330), or because the consent form or questionnaire was not completed (n = 73), 6911 (11.8%) participants were enrolled into the study. A further 214 participants who were randomised, but later found to be ineligible, were deleted from the database leaving 6697 (11.4%) participants in the analysis (Fig. 1).

figure

Figure 1. Flow diagram of the progress through the phases of the ESCAPE trial (enrolment, intervention allocation, follow-up and analysis)

Download figure to PowerPoint

Baseline characteristics

The mean age of the sample was 44.6 years, 56% (3748) were female, 5.2% (344) were non-daily smokers and the mean number of cigarettes smoked per day by daily smokers was 18.4. Few (12.7%/853) were planning to quit in the next 30 days; the largest group (47.1%/3156) were not planning to quit in the next 6 months (Table 1). Participants were categorised as lower reading level if they had qualifications of GCSE or less and did not read a traditional broadsheet newspaper, such as the Guardian, Times, Telegraph or Independent (53.3%/3572). Otherwise they were categorised as higher reading level.

Table 1. Characteristics of participants at baseline.
 GroupTotal
ControlIntervention
(n = 3357)(n = 3340)(n = 6697)
%(n)%(n)%(n)
  1. aDeprivation score was computed by scoring one point for each of the following: renting their home, no car, no qualifications, manual occupation and being unemployed or student. bDependence score was computed from the number of cigarettes per day and time from waking to first cigarette. cCategorised as low reading level if qualifications are GCSE or less and do not read a newspaper such as the Guardian, Times, Telegraph or Independent.

% Female56.8(1906)55.1(1842)56.0(3748)
 Missing2 0 2 
Mean age (SD)44.8(12.2)44.4(12.2)44.6(12.2)
 Missing6 3 9 
Mean cigarettes per day (SD)17.7(9.3)17.8(9.5)17.8(9.4)
 Missing24 25 49 
% Smoked within 30 minutes of waking62.1(2077)62.4(2073)62.2(4150)
 Missing12 16 28 
% Previously quit for more than three months48.7(1630)49.0(1633)48.8(3263)
 Missing7 4 11 
% Non-daily smokers5.4(179)5.0(165)5.2(344)
 Missing11 22 33 
Mean dependence score (cigarettes per day + time from waking) (0–7)b (SD)4.24(1.70)4.27(1.70)4.26(1.70)
 Missing27 29 56 
Intentions to quit      
Within next two weeks4.7(157)5.1(171)4.9(328)
Within next 30 days7.8(261)7.9(264)7.8(525)
Within next six months39.0(1310)41.3(1378)40.1(2688)
Not within next six months48.5(1629)45.7(1527)47.1(3156)
 Missing0 0 0 
If not planning to quit, why not?      
Too difficult21.7(729)21.1(705)21.4(1434)
Want to smoke21.9(736)20.2(674)21.1(1410)
Both2.1(69)2.0(67)2.0(136)
 Missing95 81 176 
Mean score ‘How determined are you to quit for good?’ (scale 1–5) (SD)3.19(1.21)3.26(1.20)3.22(1.21)
 Missing45 40 85 
% Living with adult smoker38.8(1299)39.3(1311)39.1(2610)
 Missing9 7 16 
Mean deprivation score (0–5)a (SD)1.69(1.16)1.67(1.15)1.68(1.16)
 Missing316 329 645 
Reading level      
Lowerc52.7(1768)54.0(1804)53.3(3572)

Follow-up response rate and attrition

The follow-up response rate, based on the analysed sample (n = 6697), was 78.8% (2644) and 75.7% (2530) in the control and intervention groups respectively (χ2 = 8.65, P = 0.003). The response rates for the different modes of response also differed significantly between the control and intervention groups (postal questionnaire 56.1%/1885 versus 48.1%/1607, telephone interview 15.9%/535 versus 19.5%/650, basic outcome 6.7%/224 versus 8.2%/273). Participants who were lost to follow-up were younger (mean age = 41.0 years versus 45.7 years, P < 0.001), more likely to be single (30.5% versus 21.7%, P < 0.001) and had a higher deprivation score (mean score = 1.88 versus 1.62, P < 0.001). They did not differ in intention or determination to quit, but did have a higher dependence score (mean score = 4.37 versus 4.22, P = 0.003) and were less likely to have previously quit for longer than 3 months (43.7% versus 50.3%, P < 0.001). None of these predictors of drop out differed significantly between groups.

Primary outcome

In the intervention group 3.2% (108/3340) reported 3-month prolonged abstinence at the 6-month follow-up compared with 2.7% (91/3357) in the control group. This corresponds to an absolute difference of 0.52% [95% CI: (−0.29%, 1.34%)] or an estimated number needed to treat (i.e. the number of smokers receiving the intervention needed to get one additional person quitting) of 192. The difference was not significant [OR = 1.20, 95% CI (0.94, 1.54), P = 0.15]. Adjustment by baseline predictors of quitting gave similar results (Table 2).

Table 2. Outcomes at the six-month follow-up.
 Control (n = 3357)Intervention (n = 3340)Absolute difference (%) (95% CI)UnadjustedAdjusteda
% (n)% (n)OR95% CIPOR95% CIP
  1. aAdjusted for gender, age, deprivation score, dependence score, intention to quit, determination to quit, previous quit attempts and living with other smokers.

Primary outcome
Three months prolonged abstinence2.7 (91)3.2 (108)0.5 (−0.29, 1.3)1.20[0.94, 1.54]0.1501.18[0.92, 1.52]0.184
Secondary outcomes
One month prolonged abstinence4.7 (158)5.5 (185)0.8 (−0.2, 1.9)1.19[0.97, 1.46]0.0991.17[0.95, 1.44]0.130
Seven day point prevalence abstinence6.3 (212)7.1 (236)0.8 (−0.4, 2.0)1.13[0.93, 1.37]0.2171.11[0.91, 1.35]0.307
Twenty-four hours point prevalence abstinence7.3 (245)8.4 (280)1.1 (−0.2, 2.4)1.16[0.98, 1.38]0.0851.15[0.96, 1.37]0.131
Quit attempt in the previous six months29.6 (995)32.3 (1078)2.6 (0.4, 4.8)1.13[1.01, 1.26]0.0261.11[0.99, 1.25]0.074

Secondary outcomes

No significant differences were found between the Intervention and Control groups on shorter periods or on point-prevalent measures of abstinence. However, the trend for higher quit rates in the intervention group was repeated in all outcomes (Table 2).

The proportion who reported making a quit attempt in the previous 6 months was significantly higher in the intervention than the control group [32.3% (1078/3340) versus 29.6% (995/3357)] [OR = 1.13, 95% CI (1.01, 1.26), P = 0.026], but the difference became weaker after adjustment [OR = 1.11, 95% CI (0.99, 1.25), P = 0.074].

Non-quitters

We also explored the effect of the intervention on prompting a quit attempt, and the length of the attempt, in participants who reported smoking daily, weekly or less than weekly at the 6-month follow-up (n = 4182). A higher proportion of participants in the intervention group than in the control group made a quit attempt in the previous 6 months [39.3% (784/1994) versus 33.6% (734/2188), P < 0.001]. The mean reduction in cigarettes per day in daily smokers was also higher in the intervention group (−2.2 versus −1.6, P < 0.001) (Table 3).

Table 3. Non-quitters i.e. participants who reported smoking daily, weekly or less than weekly at the six-month follow-up (n = 4182).
 GroupP-value*
ControlIntervention
(n = 2188)(n = 1994)
%(n)%(n)
  1. Note: caution is required when interpreting these differences as this subgroup was not representative of all those randomised, but defined post-baseline. *From χ2 test, or t-test, as appropriate.

Made a quit attempt33.6(734)39.3(784)<0.001
Length of quit attempt:     
<1 week58.7(431)54.2(425)0.079
1–4 weeks18.7(137)17.6(138) 
>4 weeks10.5(77)12.0(94) 
Missing12.1(89)16.2(127) 
Non-daily smoker5.5(121)6.1(121)0.457
Mean change from baseline in cigarettes per day in daily smokers (SD)n = 2037 n = 1856 <0.001
−1.6(5.7)−2.2(6.0)

Subgroup analysis

We compared the effectiveness of the intervention according to the reading level of the participant. Prolonged three-month abstinence rates for participants classified as of lower reading level and receiving the easier reading report were 2.6% versus 1.8% in the intervention and control groups respectively (OR = 1.50). For participants of higher reading level and receiving the standard report abstinence rates were 4.0% versus 3.8% (OR = 1.05). However, the interaction term was not statistically significant (P = 0.26).

Process evaluation

Of the participants in the intervention group, 53.3% (1781/3340) completed the 1-month follow-up assessment and thus received the complete intervention, including the tailored progress report. Of these, 4.6% (82) reported 3-month prolonged abstinence at the 6-month follow-up.

Sensitivity of main outcome results to missing data assumptions

We estimated the effect size where participants with missing outcomes were considered to have the same quit rate as the participants in the same group. Under this assumption, the quit rates for the primary outcome measure increased from 2.7% to 3.5% in the control group and from 3.2% to 4.3% in the intervention group. The intervention effect was slightly larger under this alternative assumption [OR = 1.25, 95% CI (0.97, 1.60)], but was still not significant (P = 0.078). When a wider range of missing data assumptions were considered, allowing for differential mechanism by arm, plausible scenarios showed ORs ranging from 1.06 to 1.41 (see Supporting Information).

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

ESCAPE aimed to assess the effectiveness of a brief intervention consisting of tailored advice reports when sent to a representative sample of smokers across the UK. Quit rates for the primary outcome of three months of prolonged abstinence were not significantly different between study groups. Thus, the intervention showed no effect. Quit rates in a number of different outcome measures of abstinence also showed no significant intervention effect. However, all outcome measures showed a non-significant trend toward more abstinence in the intervention group.

This trial had been designed to detect an OR of 1.42, consistent with previous findings for similar interventions [7]. The achieved sample size of 6697 allowed for 74% power only to detect such an effect of tailored material. If an OR of 1.20, as observed in this study, represents the true effect, the sample would have needed to exceed 30 000 participants. The CI around the estimate of effect size suggests that it is unlikely that the intervention has a large effect (OR 95% CI upper limit = 1.54). However, it does not provide enough evidence to rule out a small positive effect. The real intervention effect is more likely to be around OR = 1.20 than to be entirely absent. This is equivalent to an absolute difference in quit rates of 0.5%. The potential relevance of the intervention would depend on the minimum effect that could be considered relevant given the ease with which the intervention could be implemented. Some clinicians might find this small number of additional quitters in their practice worthwhile. However, the high scalability of this intervention implies a potentially valuable effect on public health; for example, if the intervention reached 100 000 smokers, we would expect 500 additional quitters.

For our primary outcome we used three months of prolonged abstinence, defined as a period of sustained abstinence during a time window immediately preceding the follow-up, and beginning at any time between the baseline screening and the follow-up. This was appropriate for a ‘cessation induction trial’, designed to increase the probability of quit attempts during a period [22], and can capture the delayed treatment effects that can occur using tailored communications, particularly in studies including early stage quitters [5, 23]. However, a single primary outcome may not make the best use of the data, thus it is important to include a range of measures which assess other possible benefits of treatment. Prompting quitting activity in smokers not motivated to quit is a valuable effect of an intervention, as this activity has the potential to eventually end with cessation. Quit attempts and the longest duration of abstinence during the follow-up can predict successful future cessation [24]. Post hoc descriptive analysis of self-reported quit attempts in non-quitters showed increases in the intervention over the control group in both the number and length of quit attempts, suggesting that the tailored intervention was stimulating cessation behaviour.

This intervention was designed to reach a wider population of smokers. A strength of this study is that by using proactive recruitment, and employing less stringent selection criteria with few exclusion categories, we enrolled a ‘broad and representative’ sample [25], which was largely representative of the smoking population of the UK in terms of motivation and socioeconomic status [15]. Further, by recruiting a diverse population of smokers, including low socioeconomic groups and those not motivated to quit, we increased the variation and external validity of our sample [26]. We would therefore expect lower quit rates than trials recruiting a more motivated population [27]. Our results are largely consistent with similar general practice-based studies of tailoring in the UK [28, 29] which enrolled a high proportion of smokers not ready to quit, and reported low overall cessation rates with small increases in the tailored letter group.

A novel feature of our intervention was that the advice reports were adapted to fit the reading ability of the recipient. While it is acknowledged that the best expert systems should be grounded in a strong theoretical basis [23], research also points to the need to tailor communications to ‘broad spectrum’ general recipient characteristics [30] of which ability to read and process information is one. Our results reflected the trend for the use of self-help materials to be less successful in lower educated groups [31]. However, a non-significant trend for our adapted intervention to be more effective in this subgroup suggests that these harder to reach groups may be receptive to help and encouragement to quit, and demonstrate the need for further work in this area.

It is not possible, in a pragmatic trial such as this, to separate out all of the components of the intervention to measure the effect of each. Thus, possible limitations of the study are that other factors could account for the modest increase in quit rates in the intervention group. These confounding factors include the additional contact received by the intervention group in the form of an accompanying GP letter with the tailored advice report and additional assessment. Another possibility is that, as participants could not be blinded to condition, the pre-trial information provided had a positive effect on quitting in smokers randomised to the intervention group. However, this is unlikely as minimum information was given to the participants regarding the nature of the intervention. An alternative explanation for the lack of a significant result is that, as all participants received the baseline questionnaire as part of the trial assessment, completing this questionnaire alone may have prompted a change in behaviour and prompted quitting in both groups [32].

Our detailed, but brief, self-help intervention produced a modest increase in quit attempts and a small number of extra quitters. While our study was not powered to detect such a small effect, from a public health perspective these small increases are important and could make a valuable contribution to lowering smoking prevalence.

Clinical trial registration

Current Controlled Trials ISRCTN05385712.

Declaration of interest

None.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

The trial was supported by funding from Cancer Research UK. We would like to thank all the GP practices who took part in the recruitment of smokers, and all of the volunteers who took part in the trial, and, in particular, Louise Letley and Nicky Fasey at the General Practice Research Framework for their help in recruiting GP practices.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Method
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
FilenameFormatSizeDescription
add12005-sup-0001-AppendixS1.doc148K

Appendix S1 Development and production of the tailored advice reports.

add12005-sup-0002-AppendixS2.doc2688K

Appendix S2 Examples of advice reports.

add12005-sup-0003-AppendixS3.doc55K

Appendix S3 Details of all participants classified as nonquitters (24 hours point prevalence) at follow-up.

add12005-sup-0004-AppendixS4.doc57K

Appendix S4 Sensitivity analyses for missing data.

Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.