As household surveys are experiencing declining response rates in the past few decades, reducing nonresponse and correcting for potential nonresponse error have been two major challenges for survey organizations. Doorstep concerns – one type of paradata – capture the interactions between interviewers and potential survey respondents during the survey introduction and reveal the concerns sampled members have expressed about the survey request and also their reasons for refusing the survey request when refusal occurs. Different organizations collect doorstep concerns in different ways. One challenge has always been how to best use and analyze these data given the inherent organizational design and collection constraints. This paper demonstrates two different ways of using doorstep concerns to characterize and to assess the reluctance of survey respondents – principal component analysis (PCA) and latent class analysis (LCA). We found that both methods produce parsimonious measures indicative of respondents’ reluctance level and the two measures are correlated with each other.