Determinants of unit nonresponse in multi-mode data collection: A multilevel analysis

Multi-mode data collection is widely used in surveys. Since several modes of data collection are successively applied in such design (e.g. self-administered questionnaire after face-to-face interview), partial nonresponse occurs if participants fail to complete all stages of the data collection. Although such nonresponse might seriously impact estimates, it remains currently unexplored. This study investigates the determinants of nonresponse to a self-administered questionnaire after having participated in a face-to-face interview.

Data from the Belgian Health Interview Survey 2013 were used to identify determinants of nonresponse to self-administered questionnaire (n = 1,464) among those who had completed the face-to-face interview (n = 8,133). The association between partial nonresponse and potential determinants was explored through multilevel logistic regression models, encompassing a random interviewer effect.

Significant interviewer effects were found. Almost half (46.6%) of the variability in nonresponse was attributable to the interviewers, even in the analyses controlling for the area as potential confounder. Partial nonresponse was higher among youngsters, non-Belgian participants, people with a lower educational levels and those belonging to a lower income household, residents of Brussels and Wallonia, and people with poor perceived health. Higher odds of nonresponse were found for interviews done in the last quarters of the survey-year. Regarding interviewer characteristics, only the total number of interviews carried out throughout the survey was significantly associated with nonresponse to the self-administered questionnaire.

The results indicate that interviewers play a crucial role in nonresponse to the self-administered questionnaire. Participant characteristics, interview circumstances and interviewer characteristics only partly explain the interviewer variability. Future research should examine further interviewer characteristics that impact nonresponse. The current study emphasises the importance of training and motivating interviewers to reduce nonresponse in multi-mode data collection.