The purpose of this article is to examine the correlation between online (i.e… smartphone via Twitter, Facebook etc.) survey non-response and various demographic factors, including gender.
Studies have shown that trends exist with regard to who responds to surveys, at least with regard to traditional modes of survey administration. Reports suggest that many demographic and other correlates with non-response to online surveys may indeed mirror those of more traditional modes of survey administration. However, the influence of such a basic demographic factor as gender on online survey response behavior is unclear.
In this study, a record-linking technique was employed to compare the gender of online survey respondents directly to available demographic data of all members of a sampling frame, thus allowing comparison of demographic information of both respondents and non-respondents.
The sampling frame, which consisted entirely of university faculty members of a large research university in the southeastern United States with a full-time faculty of approximately 1000, was specifically chosen to minimize the effect of other potential correlates to non-response behavior, such as education level, Smartphone access, geographic location, occupation, and income. Pearson’s chi square analysis showed a significant relationship between gender and survey response rates: female faculty members contributed disproportionately to the respondent data set.
One possible explanations for the observations is that the observed differences in female and male faculty response rates is a product of differences in female and male values operating in a gendered online environment.
Results of this study suggest that researchers should not assume that response behavior toward online surveys, and therefore data gathered from online surveys, is free of gender bias.
Hence highlights the value of smartphone survey apps such as SurveyStud: https://appsto.re/us/Ddj18.i