Unraveling honest responding: a systematic review on the effectiveness of social desirability bias reduction methods in survey research

Social Desirability Bias (SDB), the tendency of respondents to present themselves in socially acceptable terms, poses serious challenges for the validity of survey research. This study systematically reviewed the effectiveness of methods aimed at reducing SDB. Searches in Scopus and PsycINFO of publications from 2017 to 2021 identified a total of 121 experiments in 79 peer-reviewed papers. These experiments, conducted in over 20 Western countries, employed 13 SDB-reduction methods across more than 17 behavioral or cognitive topics. Based on 10 quality measures, the methodological quality of these experiments was typically high. There was considerable variability in the frequency of SDB-reduction methods being used and their effectiveness. The most common methods were list experiments, probability-based techniques (RRT/NRRT), face-saving strategies, survey mode, and proxy reporting. Overall, in 55% of experiments SDB was significantly reduced, with face-saving strategies demonstrating the highest efficacy. Future research should aim at replicating these findings in a wider range of (societally relevant) topics and more comprehensively testing promising less explored methods. This review highlights the importance of continuing to refine and test SDB reduction techniques to improve survey data quality.

Authors

Institutions

Publication Details

Journal
Quality & Quantity
Published
2026-03-14
DOI
https://doi.org/10.1007/s11135-026-02664-7
Primary Topic
Survey Methodology and Nonresponse
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Unraveling honest responding: a systematic review on the effectiveness of social desirability bias reduction methods in survey research

Nina van der Velden, Emma Zaal, Yfke Ongena, John Hoeks et al.
Quality & Quantity
Survey Methodology and Nonresponse
article

Unraveling honest responding: a systematic review on the effectiveness of social desirability bias reduction methods in survey research

Nina van der Velden, Emma Zaal, Yfke Ongena, John Hoeks, Dan Loughnan
article en

Abstract

Social Desirability Bias (SDB), the tendency of respondents to present themselves in socially acceptable terms, poses serious challenges for the validity of survey research. This study systematically reviewed the effectiveness of methods aimed at reducing SDB. Searches in Scopus and PsycINFO of publications from 2017 to 2021 identified a total of 121 experiments in 79 peer-reviewed papers. These experiments, conducted in over 20 Western countries, employed 13 SDB-reduction methods across more than 17 behavioral or cognitive topics. Based on 10 quality measures, the methodological quality of these experiments was typically high. There was considerable variability in the frequency of SDB-reduction methods being used and their effectiveness. The most common methods were list experiments, probability-based techniques (RRT/NRRT), face-saving strategies, survey mode, and proxy reporting. Overall, in 55% of experiments SDB was significantly reduced, with face-saving strategies demonstrating the highest efficacy. Future research should aim at replicating these findings in a wider range of (societally relevant) topics and more comprehensively testing promising less explored methods. This review highlights the importance of continuing to refine and test SDB reduction techniques to improve survey data quality.

Quality & Quantity
Radboud University Nijmegen (NL), University of Groningen (NL)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Reduced inequalities
Openalex Percentile: Top 27%
Survey Methodology and Nonresponse
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.