Schulz et al. BMC Public Health 2011, 11:108 http://www.biomedcentral.com/1471-2458/11/108 Power analysis calculations differ per behaviour. Estima- tions for finding effects on the lifestyle behaviours of smoking and alcohol consumption were the most con- servative power analyses resulting in the greatest num- ber of respondents needed. Since approximately 25% to 30% of the population smoke and almost similar percen- tages are estimated for non-compliance with the alcohol guideline [7], sample size calculations are highly deter- mined by these two groups. In order to be able to find a significant difference of 10% in quit rates and improved behaviour between the conditions, power calculations (alpha=.80; p=.05) indicate that 219 smoking persons per cell are needed, resulting in a total of 657 smokers. Hence, if approximately 25% of the adult population smokes this requires a total study sample of 2,826 per- sons. A similar conclusion can be drawn for the persons not adhering to the Dutch alcohol recommendations. Correcting for dropout this indicates that the total sam- ple size for this study will be approximately 3,285 per- sons. The sample will be sufficient to assess changes in the other behaviours (fruit and vegetable consumption and physical activity). Attrition prevention Different strategies are used in order to prevent attrition and to encourage participation in the long run. First, participants are eligible to win prizes. Participants com- pleting the study stand a chance to win one of 300 prizes of 50 Euros. Second, half of the respondents of the experimental groups receive e-mail prompts, includ- ing invitations to visit the tailoring programme, every three months, in order to be able to analyse whether pro-active prompting will enhance visiting the website and using computer tailored feedback more intensively. Third, new information is placed on the website monthly in order to keep it up to date and make it attractive for people to re-visit the website. Statistical analyses General descriptive statistics will be used to describe the characteristics of the participants and the main findings concerning the public health guidelines. With regard to the assessment of behavioural effects and differences between the three groups, logistic as well as linear regression analyses will be performed using Statistical Package for the Social Sciences (SPSS) version 15. With regard to the process evaluation, descriptive statistics will be used, such as frequencies, means, standard devia- tions and ranges. Satisfaction with the programme and ideas for improvement will also be analysed by summar- izing the answers to the open-ended question and com- paring different attitudes and suggestions. In order to explore potential differences between groups (e.g., low Page 7 of 9 SES versus high SES, age groups, gender), regression techniques and latent cluster analyses will be used. Discussion The results of this study are of importance for the future development and implementation of CT pro- grammes, which aim at stimulating healthy lifestyles in order to prevent chronic diseases. Positively changing a set of health risk behaviours, i.e., smoking, high alcohol consumption, bad nutrition and physical inactivity, is becoming increasingly common since these changes are relevant for the primary prevention of cardiovascular related diseases and cancer [1,2]. Due to the target of several behaviours and health problems, by using a tai- lored web-based programme, these kinds of programmes are considered to be potentially cost-effective [11]. Internet-based health education programmes have become popular in recent years. To our knowledge, however, few were tested in a RCT to analyse effects on multiple behaviours. Addressing smoking, alcohol con- sumption, fruit and vegetable intake, and physical activ- ity at the same time, is one fundamental part of recent developments. In addition, we compare a simultaneous behaviour tailoring approach with a sequential beha- viour tailoring approach. Hence, we will experimentally test which tailoring lifestyle approach is more effective and appreciated. This study will thus yield results about the need for differential lifestyle approaches. An optimal use of (one of) the different strategies could increase the effectiveness of web-based CT lifestyle programmes. Research is also important in order to assess whether the effectiveness and appreciation of the programme dif- fers between various subgroups. Furthermore, a unique element of this project is that our CT programme is offered as an additional service of the RHAs in the Dutch regions of North-Brabant and Zeeland within the regular health monitoring they pro- vide to adults. The integration of the CT programme to the Adult Health Monitor 2009 brings along various advantages. First, the RHAs may extend and improve their health education task by offering tailored feedback regarding lifestyle behaviours to their respondents. Sec- ond, the personal advice may be an extra stimulus for people to participate in the Adult Health Monitor. Third, the Adult Health Monitor of the two provinces has a total reach of nearly 100,000 inhabitants. Due to the integration of our CT programme into the ‘Adult Health Monitor’, a large number of people within the Dutch population may be reached. Acknowledgements This study is funded by ZonMw, the Netherlands Organisation for Health Research and Development (120610012).