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Self-protecting responses in randomized response designs: A survey on intimate partner violence during the coronavirus disease 2019 pandemic

DSEID
DSEID-001-9804481
DOI
10.1177/00491241211043138
Journal
Sociological Methods & Research
Publisher
SAGE Publications
Published
2024-2
Status
failed

Abstract

Randomized response techniques (RRTs) are applied to reduce response biases in self-report surveys on sensitive research questions (e.g., on socially undesirable characteristics). However, there is evidence that they cannot completely eliminate self-protecting response strategies. To address this problem, there are RRTs specifically designed to measure the extent of such strategies. Here we assessed the recently devised unrelated question model—cheating extension (UQMC) in a preregistered online survey on intimate partner violence (IPV) victimization and perpetration during the first contact restrictions as containment measures for the outbreak of the coronavirus disease 2019 pandemic in Germany in early 2020. The UQMC accounting for self-protecting responses described the data better than its predecessor model which assumes instruction adherence. The resulting three-month prevalence estimates were about 10% and we found a high proportion of self-protecting responses in the group of female participants queried about IPV victimization. However, unexpected results concerning the differences in prevalence estimates across the groups queried about victimization and perpetration highlight the difficulty of investigating sensitive research questions even using methods that guarantee anonymity and the importance of interpreting the respective estimates with caution.

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Metadata

Title
Self-protecting responses in randomized response designs: A survey on intimate partner violence during the coronavirus disease 2019 pandemic
Delta ID
DSEID-001-9804481
Authors
Fabiola Reiber, Donna Bryce, Rolf Ulrich
Abstract source
crossref
Source URL
https://opus.bibliothek.uni-augsburg.de/opus4/files/104315/104315.pdf
Access
open_repository
Licence
cc-by
PDF SHA-256
TEI SHA-256
GROBID

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WhenEventFieldOldNew
2026-06-18 19:37:53.011249+00:00identifier_assignedDSEIDDSEID-001-9804481