Mail merge can be used to create personalized questionnaires in complex surveys - Taljaard, Monica; Chaudhry, Shazia H; Brehaut, Jamie C; Weijer, Charles; Grimshaw, Jeremy M (Université d'Ottawa | University of Ottawa, 2015)
Abstract Background Low response rates and inadequate question comprehension threaten the validity of survey results. We describe a simple procedure to implement personalized—as opposed to generically worded—questionnaires in the context of a complex web-based survey of corresponding authors of a random sample of 300 published cluster randomized trials. The purpose of the survey was to gather more detailed information about informed consent procedures used in the trial, over and above basic information provided in the trial report. We describe our approach—which allowed extensive personalization without the need for specialized computer technology—and discuss its potential application in similar settings. Results The mail merge feature of standard word processing software was used to generate unique, personalized questionnaires for each author by incorporating specific information from the article, including naming the randomization unit (e.g., family practice, school, worksite), and identifying specific individuals who may have been considered research participants at the cluster level (family doctors, teachers, employers) and individual level (patients, students, employees) in questions regarding informed consent procedures in the trial. The response rate was relatively high (64 %, 182/285) and did not vary significantly by author, publication, or study characteristics. The refusal rate was low (7 %). Conclusion While controlled studies are required to examine the specific effects of our approach on comprehension, quality of responses, and response rates, we showed how mail merge can be used as a simple but useful tool to add personalized fields to complex survey questionnaires, or to request additional information required from study authors. One potential application is in eliciting specific information about published articles from study authors when conducting systematic reviews and meta-analyses.