Social Desirability Bias in CATI, IVR, and Web Surveys: The Effects of Mode and Question Sensitivity

Kreuter, Frauke; Presser, Stanley; Tourangeau, Roger

doi:10.1093/poq/nfn063

Cited by 978 publications

(649 citation statements)

References 7 publications

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“…So far, there are few studies explicitly focusing on the accuracy of self-reported behaviors across survey modes by validating respondents' answers against objective criteria. The available evidence suggests that the identified increase in prevalence rates is also accompanied by an increase in accuracy (e.g., Hewett et al, 2008;Kreuter, Presser, & Tourangeau, 2008;Langhaug et al, 2010;van Griensven et al, 2006). For example, in a mode experiment Kreuter and colleagues (2008;see also Sakshaug, Yan, & Tourangeau, 2010) validated self-reported academic performance of students against available university records.…”

Section: Accuracy Of Self-reported Sensitive Behaviorsmentioning

confidence: 99%

Disclosure of sensitive behaviors across self-administered survey modes: a meta-analysis

2014

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In surveys, individuals tend to misreport behaviors that are in contrast to prevalent social norms or regulations. Several design features of the survey procedure have been suggested to counteract this problem; particularly, computerized surveys are supposed to elicit more truthful responding. This assumption was tested in a meta-analysis of survey experiments reporting 460 effect sizes (total N =125,672). Self-reported prevalence rates of several sensitive behaviors for which motivated misreporting has been frequently observed were compared across self-administered paper-andpencil versus computerized surveys. The results revealed that computerized surveys led to significantly more reporting of socially undesirable behaviors than comparable surveys administered on paper. This effect was strongest for highly sensitive behaviors and surveys administered individually to respondents. Moderator analyses did not identify interviewer effects or benefits of audio-enhanced computer surveys. The meta-analysis highlighted the advantages of computerized survey modes for the assessment of sensitive topics.

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Section: Accuracy Of Self-reported Sensitive Behaviorsmentioning

confidence: 99%

Disclosure of sensitive behaviors across self-administered survey modes: a meta-analysis

2014

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“…A mail survey comparison offered certain other advantages for the present study. For one, some of the questions were relatively sensitive, for which self-administered modes generally provide superior measures (Kreuter et al 2008). For another, interviewer-administered surveys can suffer from interviewer-related effects other than social desirability bias (and in face-to-face surveys these are confounded with clustering in the sample design).…”

Section: Discussionmentioning

confidence: 99%

“…The problem is that in practice this is rarely feasible for researchers, as it requires "an estimate of the parameter that is essentially error free" (Biemer 2010, 826). For example, to assess measurement bias, external records can be used to assess the accuracy of respondents' self-reports (e.g., Olson 2006;Kreuter et al 2008;Sakshaug et al 2010;Tourangeau et al 2010). To assess nonresponse bias, these auxiliary data are needed for both respondents and nonrespondents (e.g., Klausch et al 2015a;Kreuter et al 2010;Kappelhof 2013).…”

Section: Estimating the Effect Of Mixing Modes On Survey Errors And Amentioning

confidence: 99%

Estimating Components of Mean Squared Error to Evaluate the Benefits of Mixing Data Collection Modes

Roberts

Vandenplas

2017

Journal of Official Statistics

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Mixed mode data collection designs are increasingly being adopted with the hope that they may reduce selection errors in single mode survey designs. Yet possible reductions in selection errors achieved by mixing modes may be offset by a potential increase in total survey error due to extra measurement error being introduced by the additional mode(s). Few studies have investigated this empirically, however. In the present study, we compute the Mean Squared Error (MSE) for a range of estimates using data from a mode comparison experiment. We compare two mixed mode designs (a sequential web plus mail survey, and a combined concurrent and sequential CATI plus mail survey) with a single mode mail survey. The availability of auxiliary data on the sampling frame allows us to estimate several components of MSE (sampling variance, non-coverage, nonresponse and measurement bias) for a number of sociodemographic and target variables. Overall, MSEs are lowest for the single mode survey, and highest for the CATI plus mail design, though this pattern is not consistent across all estimates. Mixing modes generally reduces total bias, but the relative contribution to total survey error from different sources varies by design and by variable type.

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“…13 Using this matching method, we are able to control for geographic, temporal, and polling firm-specific effects to the maximum extent possible. Various studies have identified many different types of general survey mode effects (Tourangeau and Smith 1996;Krysan et al 1994;Fricker et al 2005;Kreuter et al 2008), and moreover, the way in which a candidate's gender interacts with these previously identified modes effects is entirely unknown. In light of this, the use of matched cases becomes even more crucial.…”

Section: Methodsmentioning

confidence: 99%

I’m Not Voting for Her: Polling Discrepancies and Female Candidates

Stout

Kline

2010

Polit Behav

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Although there is a large literature on the predictive accuracy of preelection polls, there is virtually no systematic research examining the role that a candidate's gender plays in polling accuracy. This is a surprising omission given the precipitous growth of female candidates in recent years. Looking at Senate and Gubernatorial candidates from 1989 to 2008 (more than 200 elections in over 40 states), we analyze the accuracy of pre-election polls for almost the complete universe of female candidates and a matched sample of white male cases. We demonstrate that pre-election polls consistently underestimate support for female candidates when compared to white male candidates. Furthermore, our results indicate that this phenomenon-which we dub the Richards Effect, after Ann Richards of Texas-is more common in states which exhibit traits associated with culturally conservative views of gender issues.

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Social Desirability Bias in CATI, IVR, and Web Surveys: The Effects of Mode and Question Sensitivity

Cited by 978 publications

References 7 publications

Disclosure of sensitive behaviors across self-administered survey modes: a meta-analysis

Disclosure of sensitive behaviors across self-administered survey modes: a meta-analysis

Estimating Components of Mean Squared Error to Evaluate the Benefits of Mixing Data Collection Modes

I’m Not Voting for Her: Polling Discrepancies and Female Candidates

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