The influence of interviewers on survey responses among female sex workers in Zambia

Abstract

BackgroundInterviewers 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.MethodsWe analyzed data 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. We used hierarchical regression models 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.ResultsModel variance (ICC) at the interviewer level was over 15% for most topics. ICC was lower for socio-demographic and cognitively simple questions, and highest for sexual behaviour, substance use, violence and psychosocial wellbeing questions. Respondents reported significantly lower socioeconomic status and more sex-work related violence to female interviewers. Not accounting for interviewer identity in regressions predicting HIV self-test behaviour led to coefficients moving from non-significant to significant.ConclusionsWe found substantial interviewer-level effects for prevalence and associational outcomes among Zambian FSWs, particularly for sensitive questions. Our 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.Trial registrationclinicaltrials.gov NCT02827240. Registered 11 July 2016.Electronic supplementary materialThe online version of this article (10.1186/s12874-019-0703-2) contains supplementary material, which is available to authorized users.

Language analysis of spontaneous descriptions of restless legs syndrome: Gender differences?

“…Another strength is the inclusion of a large sample of consecutive RLS patients, with a sex ratio similar to the one reported for RLS prevalence in epidemiological data (Berger et al, 2004 ; Didriksen et al, 2017 ; Hening et al, 2004 ; Högl et al, 2005 ; Kim et al, 2019 ). A possible limitation is that all patients were interviewed by a female investigator: interviewer’s gender has been reported to cause a bias in responses about sensitive experiences or behaviours (which are reported more frequently to women by women (Harling et al, 2019 ) and to female voices by men (Dykema et al, 2012 )), or substance abuse (which seems to be reported more often to men by both women and men; Heeb & Gmel, 2001 ; Houle et al, 2019 )). Although men and women talk about the same when in same‐gender dyads, women talk less while talking to men, whereas men talk more when talking to women than when talking to men (Mulac, 1989 ).…”

Pelvic floor muscle training programme in pregnant Nepalese women—a feasibility study

“…This might potentially have influenced the responses, as different interviewer personalities and characteristics might generate different response patterns (196). The importance of careful training and response monitoring to minimise inter-interviewer variation has previously been reported (197). Thus, to avoid bias, the research assistants in our study were thoroughly trained prior to the data collection, and clearly instructed to ask the same questions in a standardised way, without discussing any responses.…”

Does interviewer gender influence a mother’s response to household surveys about maternal and child health in traditional settings? A qualitative study in Bihar, India

“…Considerable debate focuses on whether matching interviewer and respondent characteristics improves the accuracy of interview data [2,3]. This concern is particularly relevant in household surveys that obtain selfreported information about sensitive topics through face-to-face interviews or in surveys that target respondents from marginalized populations [1,4,5].…”

“…While it may seem logical that matching interviewer and respondent should reduce social distance and the potential for response error, evidence of interviewer effects across studies on response rates and response quality are inconsistent [1,2,[5][6][7][8][9]. Several methodological studies show that interviewer effects vary by country and geographic area; however, little is known how cultural norms or social context influence the interviewer-respondent rapport and lead to measurable interviewer effects [1,3,4,10,11]. Few qualitative studies have explored respondents' perceptions of the interview process, in particular the acceptability of an interviewer's gender or how social norms influence female respondent behaviour and survey responses [12].…”

“…The principal concern is whether observable characteristics of an interviewer (e.g., race, gender, age) or their perceived social status can bias responses to survey questions [ 1 ]. The literature considers three types of interviewer effects in survey research: non-participation (refusal to participate), nonresponse (refusal to answer a question) and response quality (accuracy of the response) [ 3 , 4 ]. Methodological research carried out in high-income countries has focused on item nonresponse and strategies to control response bias using improved survey design and data analysis techniques [ 6 ].…”