Interviewers can substantially affect self-reported data. This may be due to random variation in
interviewers’ ability to put respondents at ease or in how they frame questions. It may also be due to systematic
differences such as social distance between interviewer and respondent (e.g., by age, gender, ethnicity) or different
perceptions of what interviewers consider socially desirable responses. Exploration of such variation is limited,
especially in stigmatized populations.
Data was analyzed from a randomized controlled trial of HIV self-testing amongst 965 female sex workers
(FSWs) in Zambian towns. In the trial, 16 interviewers were randomly assigned to respondents. Hierarchical
regression models were used to examine how interviewers may both affect responses on more and less sensitive topics, and confound associations between key risk factors and HIV self-test use.
Substantial interviewer-level effects for prevalence and associational outcomes among Zambian
FSWs were found, particularly for sensitive questions. The findings highlight the importance of careful training and response monitoring to minimize inter-interviewer variation, of considering social distance when selecting interviewers and of evaluating whether interviewers are driving key findings in self-reported data.
Authors: Guy Harling, Michael M. Chandra, Katrina F. Ortblad, Magdalene Mwale, Steven Chongo, Catherine Kanchele, Nyambe Kamungoma, Leah G. Barresi, Till Bärnighausen, Catherine E. Oldenburg