Impact of question topics and filter question formats on web survey breakoffs. (November 2022)

• Record Type: Journal Article
• Authors: Chen, Zeming; Cernat, Alexandru; Shlomo, Natalie; Eckman, Stephanie
• Is Part Of: International journal of market research. Volume 64:Number 6(2022)
• Page Start: 710
• Page End: 726
• Publication Date: 2022-11
• Subjects: web surveys -- breakoff timing -- survival model -- questionnaire design -- experimental design; Marketing research -- Periodicals; 658.8305
• DOI: 10.1177/14707853211068008
• Languages: English
• ISSNs: 1470-7853

Abstract

Web surveys have become increasingly popular over the last decade, but they tend to suffer from breakoffs, which take place when respondents start the survey but do not complete it. Many studies have investigated the factors impacting breakoffs, but they often ignored the breakoff timing and gave scant attention to two factors: question topics and filter question formats (grouped vs. interleafed as defined by whether filter questions are presented upfront or not). Using survival analysis, this study first identifies when breakoffs are more likely to happen and what are the time-varying predictors of breakoffs. Then, by using a web survey that experimentally manipulates the filter question format and randomly orders the question topic, this study investigates the effect of question topics and filter question formats on the breakoff event and its timing. We find that most breakoffs tend to happen at the beginning of the questionnaire and at the place where a new question topic is introduced. While item nonresponse is associated with more breakoffs, it is surprising to see that open-ended and long questions are associated with a lower breakoff risk. Additionally, we discover that grouping the filter questions leads to fewer breakoffs at the beginning compared to the interleafed counterpart, but the breakoff risk in the grouped format catches up quickly when respondents realise their previous answers will trigger more questions. This study also shows that questions about insurance have more breakoffs while questions on demographics and income have fewer breakoffs despite their sensitivity level.