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Introduction: Smoking remains a significant public health problem and is a leading cause of preventable morbidity and mortality around the world. By combining the behavioral intervention principles used in specialist services with the high reach rates of public health interventions, personal tailored self-help cessation intervention provides a potential economical method for improving reach and effectiveness., Methods: Cost-effectiveness analysis is performed alongside a randomized controlled trial to compare the computer-tailored self-help intervention with a generic self-help intervention in smoking cessation. A Markov model was developed to extrapolate lifetime cost-effectiveness by combining trial data with estimates from the literature., Findings: In the short term, smokers in the intervention group gained 0.0006 (95% CI = -0.0024 to 0.0036) quality-adjusted life years (QALYs) more than those in the control group at an increased cost of about £9 per person (95% CI = £5-£12). This yielded an incremental cost-effectiveness ratio (ICER) of £14,432/QALY. Precision of the ICER estimates was assessed by 5,000 bootstrapping replications. The probability that the intervention was cost effective was 54% (58%) at a cost-effectiveness threshold of £20,000(£30,000) per QALY. The Markov model showed that simulating lifetime outcomes improved the cost-effectiveness ratio (£9,700/QALY) in favor of the tailored intervention. The intervention would have a 55%-57% chance of being more cost effective than nontailored intervention at the willingness-to-pay threshold of £20,000-30,000/QALY., Conclusions: The computer-tailored intervention appears slightly more likely to be cost effective than the generic self-help intervention in smoking cessation, in both the short term and the long term, but caution is required given the considerable uncertainty surrounding the estimates.

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., (© 2012 The Authors, Addiction © 2012 Society for the Study of Addiction.)

Objectives: To describe the characteristics of a sample of smokers recruited proactively into a smoking cessation trial, and to compare these characteristics with the wider population using data from the General Household Survey (GHS) and National Statistics Omnibus Survey., Study Design: Sample recruited for a randomized controlled trial., Methods: Between August 2007 and October 2008, 123 general practices mailed questionnaires to smokers in the U.K. identified from computer records. Smokers willing to participate in a trial of personalized computer-tailored feedback returned the questionnaires to the research team. The characteristics of the sample were compared with the wider population using data from the GHS and National Statistics Omnibus Survey, and Index of Material Deprivation scores., Results: A response rate of 11.4% (n = 6697) was achieved. The sample was demographically similar to the population sample, with an even distribution of participants from areas of both high and low deprivation. The sample was more dependent than the GHS sample, but less dependent than clinic samples. Distribution by motivation and readiness to quit was similar to population estimates., Conclusions: Public health strategies targeting the entire population of smokers are needed to counter the low recruitment rates resulting from the traditional reactive methods of recruitment to smoking cessation studies. Using computerized records to identify and contact patients who are smokers is a simple method of recruiting a larger, more representative sample of smokers., (Copyright © 2011 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.)

Background: Recruiting smokers to smoking cessation trials is challenging and participation rates are often low. Consequently, the interventions evaluated may fail to reach a broad spectrum of the target population, thus compromising the generalizability of the findings. Brief interventions, using proactive recruitment, are likely to attract a broader and more representative proportion of the population., Objective: We explored the factors that influenced recruitment into a trial evaluating computer-tailored feedback reports that aimed to help smokers to quit [the ESCAPE (Effectiveness of computer-tailored Smoking Cessation Advice in Primary Care) study] in order to investigate the possibilities for increasing recruitment into smoking cessation trials., Methods: Current cigarette smokers, identified from GP records, were invited to participate in the study. The main outcome measure was the recruitment rate, i.e. the proportion of participants who responded and were randomized to one of the intervention groups. Predictor variables included geographical region, level of deprivation, practice characteristics and the number and timing of mailings of questionnaires., Results: The recruitment rate varied by practice (2.5-19.8%) and differed significantly between regions (from 16.3% in Scotland to 8.4% in London, P < 0.001). Recruitment decreased significantly by 1.1% between the lowest and highest quintiles of deprivation (P = 0.012), measured by Index of Multiple Deprivation scores, and decreased by 1.33% for every extra 10% smokers identified within a practice population (P = 0.010). Sending reminders increased recruitment by 7.5% (P < 0.001). Multivariable analysis showed region and length of time between mailings were the main predictors of recruitment., Conclusions: Proactive recruitment methods can increase participation in smoking cessation trials and weighting the target sample in favour of more deprived areas will recruit a more representative sample. The number and timing of mailings to potential participants can also increase recruitment.