Increasing response to a postal survey of sedentary patients – a randomised controlled trial [ISRCTN45665423]

Participants were randomised to receive a pre-warning letter or no pre-warning letter, seven days before sending the main questionnaire. The main questionnaire included a covering letter and pre-paid return envelope. After seven days, non-responders were sent a reminder letter and seven days later, another reminder letter with a further copy of the questionnaire and return envelope.627 adults, with a mean age of 48 years (SD 13, range 18 to 78) of whom 69.2% (434/627) were women, were randomised. 49.0% (307/627) of patients were allocated to receive a pre-warning letter and 51.0% (320/627) no pre-warning letter, seven days in advance of posting the main questionnaire. The final response rate to the main questionnaire was 30.0% (92/307) amongst those sent a pre-warning letter and 20.9% (67/320) not sent a pre-warning letter, with an adjusted odds ratio of 1.60 (95% CI 1.1, 2.30).The relatively low cost method of sending a pre-warning letter had a modest impact on increasing response rates to a postal questionnaire sent to a group of patients for whom a low response rate was anticipated. Investigators should consider incorporating this simple intervention when conducting postal surveys, to reduce the potential for nonresponse bias and to increase the study power. Methods other than postal surveys may be needed however when a low response rate to postal surveys is likely.Postal surveys are routinely used to obtain information from patients and groups within the general population, over a range of topics. Postal surveys are a cost-efficient method compared with intensive methods such as face-to-face interviews and capable of obtaining systematically, information on many thousands of people. A key quality component of postal surveys relates to the number of people sampled, and the proportion returning a completed useable questionnaire [1]. Lower response rates can reduce the statistical power of the study, and mask statistically significant relationships, which 'truly' e