MacMillan et al. BMC Public Health 2011, 11:120 http://www.biomedcentral.com/1471-2458/11/120 Data management Quantitative data were entered into a Microsoft Excel (Microsoft Corp., Redmond, WA, USA) database and stored on a secure network drive. All questionnaire data were double-entered and checked by a member of the research team. Qualitative data were audio-recorded, transcribed verbatim and anonymised. Hard copies of questionnaire data and the focus group and interview transcripts were kept in a secure filing cabinet. Data analysis Data collection was completed in December 2010. Infer- ences about the effect of the intervention will be drawn from comparisons between groups in outcome measure- ments at baseline and at 12 weeks. Follow-up data at 24 weeks will be used in the immediate group to assess whether any benefits are maintained; in the delayed group follow-up data will provide a secondary assess- ment of the impact of the intervention. Data will be analysed on an intention to treat basis, that is according to the randomisation rather than whether or not the intervention was received or completed. In the first instance, missing data will not be imputed, though the sensitivity of the main findings will be assessed under alternative assumptions regarding missing values (such as last observation carried forward). Similarly, outlying values (e.g. very low step counts) will not be excluded from initial analyses, though analyses will be repeated following the exclusion of outcome values that fall out- side plausible ranges. Qualitative data will be themati- cally analysed, which involves coding participants’ speech into categories that summarise and systemise the content of the data [62]. NVivo 8 software (QSR Inter- national, Melbourne, Australia) will be used to aid cod- ing and data retrieval. Discussion This paper describes the WEW65+ study rationale and design, including details of the intervention, the out- come measures and recruitment process. WEW65+ will provide information on the delivery of a walking inter- vention through a primary care setting specifically via a general practice (feasibility element of the study) as well as the efficacy of the intervention in men and women aged ≥65 years (pilot element of the study). The study will address several evidence gaps: a) exploration of the efficacy of an intervention to increase walking participa- tion using an objective measure of physical activity in a randomised controlled trial with an older adult popula- tion in the UK; b) determination of the achievability of the physical activity recommendation for older adults; c) examination of the feasibility of recruiting older adults via a general practice; and d) assessment of the delivery Page 9 of 12 of the walking intervention in a primary care setting (general practice) by a practice nurse. Strengths Findings from this study will determine if the interven- tion is efficacious and feasible and thus if it should then be tested in a larger trial of effectiveness, in real-world conditions (based on current guidance on evaluation of complex interventions [41]). The framework objectives for phase II pilot and feasibility studies are as follows: to have confidence that the intervention can be delivered as planned; to be able to make ‘safe assumptions about effect sizes and variability;’ and to be confident of recruitment and retention rates. The Consolidated Stan- dards for Reporting Trials (CONSORT), guidelines were designed to improve the design and reporting of rando- mised controlled trials [63]. By following these guide- lines the process of putting research into practice can be enhanced [49]. Principles from the CONSORT guide- lines were used to strengthen the design of this study. Objective measures of physical activity In this study the intervention is centred round the cur- rent physical activity recommendation for older adults and will inform whether this recommendation is achievable. Physical activity participation is measured using more than one objective measure in this study which will allow the comparison of step counts and other physical activity output (e.g., step rate and walk- ing intensity) from the devices and provides a back-up should one device fail or work incorrectly. In addition to measuring physical activity, the activPAL measures sedentary time and these data will help to determine whether a recommendation for older adults on seden- tary behaviour is required, and whether a walking intervention has a supplementary effect on sedentary behaviour. Well-being assessment The collection of well-being and functional ability data (mood, quality of life, perceived motor-efficacy and loneliness) are strengths of this study as these areas of health are extremely important in older people [2,12]. Well-being data will also help facilitate cost-effectiveness analysis of the intervention in the future. Mixed methods approach and lessons from previous research This study combines quantitative and qualitative ele- ments in order to address the research questions as comprehensively as possible. Multi-disciplinary team The research team for this project consisted of 13 mem- bers from various disciplinary backgrounds (including physical activity researchers, psychologists, a sociologist, a measurement specialist, a general practitioner and a