Mitigating social desirability bias in Likert-scale surveys: a methodological review for social and public policy studies

Abstract

Abstract

Purpose This study examines how social desirability (SD) bias undermines the validity of Likert-type surveys in sociology and social policy research, and provides a methodological review of its psychological foundations, empirical manifestations, and mitigation strategies for sensitive survey contexts. Design/methodology/approach A narrative methodological synthesis was conducted using PsycINFO, Scopus, Web of Science, and Google Scholar (1960–2026). Findings are organized into four mitigation families, including questionnaire design, timing-based interventions, indirect questioning, and analytical controls, and are evaluated against Stocké (2004) three-condition framework, which identifies non-anonymity, approval-seeking disposition, and item desirability differentials as necessary co-conditions for SD bias activation. Findings SD bias arises from both deliberate impression management and automatic self-deception, distorting correlations, group means, and prevalence estimates in policy-relevant surveys. Experimental evidence reveals a curvilinear relationship between response time and SD bias, with both fast- and slow-responding amplifying bias, undermining time-pressure interventions as a general remedy. Layered combinations of anonymity assurances, indirect questioning, careful item wording, and statistical controls provide more robust, though still partial, protection. Originality/value Unlike prior reviews that treat psychological mechanisms and practical mitigation in isolation, this study integrates both within a single theoretically anchored framework spanning classical instruments and emerging approaches, including evaluative neutralization, ICT, and digital behavioral detection. It presents a structured matrix comparing mitigation techniques by their strengths, trade-offs, and implementation requirements, and provides a theory-derived rationale for why layered strategies that target different triggering conditions simultaneously offer greater practical robustness than any single technique.