2026-04-16T10:12:55Z https://datacatalogue.cessda.eu/oai-pmh/v0/oai

328c4d9511d6da93c56ec1f503e584f9e15d612146ecdb4e45c6087aabf85092 2025-08-11T02:12:35Z language:enopenaire_data

No Introduction Necessary: Face-saving Answer Options Outperform Preambles in Reducing Social Desirability Bias No Introduction Necessary: Face-saving Answer Options Outperform Preambles in Reducing Social Desirability Bias doi:10.17026/SS/20QIVP E. Zaal 2022 PGW.20.024 DANS Data Station Social Sciences and HumanitiesEmma Zaal 2025 Arts and HumanitiesSocial SciencesSocial Desirability Bias, Face-saving, Survey research This dataset contains all files necessary to replicate the study "No Introduction Necessary: Face-saving Answer Options Outperform Preambles in Reducing Social Desirability Bias" (RMD, word & Excel files) Social Desirability Bias (SDB), providing a favorable image of oneself in self-reports, is a persistent problem in survey research on sensitive topics. However, face-saving approaches appear promising in discouraging SDB. Specifically, face-saving survey item formulations aim to reduce the threat of judgment for norm-violations, thereby fostering a safer context for self-disclosure. This experimental study examined the use of face-saving to elicit more truthful responses to yes/no questions using a quota sample representative of the Dutch population. We included face-saving preambles that excused for, or normalized sensitive behaviors (e.g., “It can easily happen that the limit for legal driving is exceeded when consuming alcohol”). We also included face-saving response options using degrees of truth (“occasionally”) or justifications for norm transgressions (e.g., “only when there was no other option”). There were three objectives. First, the design included a replication of a face-saving study regarding COVID-19, where we assessed the efficacy of a condition that combined a face-saving preamble with face-saving answer options (N=303) against a control condition without any face-saving elements (N=284). Second, we extended the replication’s design by including conditions to measure the effects of offering face-saving preambles (N=281) and offering face-saving answer options in isolation (N=283). Third, we investigated the effectiveness of face-saving using novel operationalizations on additional topics, including sustainability and responsible driving. The replication confirmed the effectiveness of the combined face-saving strategy. The extension that included all conditions (Ntotal=1151), revealed that offering face-saving answer options reduced SDB significantly, up to 23%. There was no main effect of including a preamble, nor was there an interaction effect of the two manipulations. These findings highlight the critical role that face-saving response options might play in improving the accuracy of self-reported data, while calling into question the usefulness of including face-saving preambles. 20222022 survey data https://ssh.datastations.nl/oai doi:10.17026/SS/20QIVP 2025-08-05T00:01:35Z ddi:codebook:2_5