Mindset, Moment, and Measurement: Addressing Bias and Response Instability in Questionnaire-Based Social Science Research

Questionnaires are indispensable in social science research, yet they are vulnerable to the instability of human cognition and emotion. Respondents’ answers often depend on their transient mindset, emotional state, or situational context, which may not reflect their enduring beliefs or behaviours. This paper examines the problem of response bias arising from mindset-dependent answering and evaluates whether such biases undermine the validity of social science research. Drawing upon the works of Choi & Pak (2005), Bogner & Landrock (2016), and Bhattacherjee (2012), among others, it argues that while bias cannot be completely eradicated, it can be minimised through methodological rigour, triangulation, and reflexive interpretation. The study concludes that social sciences do not fail due to bias; rather, their strength lies in the reflexive awareness and transparent management of human variability in responses.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-22
DOI
https://doi.org/10.5281/zenodo.17680100
Primary Topic
Survey Methodology and Nonresponse
Type
article
Field-Weighted Citation Impact
0.00
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article

Mindset, Moment, and Measurement: Addressing Bias and Response Instability in Questionnaire-Based Social Science Research

Zenodo (CERN European Organization for Nuclear Research)
Survey Methodology and Nonresponse
article

Mindset, Moment, and Measurement: Addressing Bias and Response Instability in Questionnaire-Based Social Science Research

article en

Abstract

Questionnaires are indispensable in social science research, yet they are vulnerable to the instability of human cognition and emotion. Respondents’ answers often depend on their transient mindset, emotional state, or situational context, which may not reflect their enduring beliefs or behaviours. This paper examines the problem of response bias arising from mindset-dependent answering and evaluates whether such biases undermine the validity of social science research. Drawing upon the works of Choi & Pak (2005), Bogner & Landrock (2016), and Bhattacherjee (2012), among others, it argues that while bias cannot be completely eradicated, it can be minimised through methodological rigour, triangulation, and reflexive interpretation. The study concludes that social sciences do not fail due to bias; rather, their strength lies in the reflexive awareness and transparent management of human variability in responses.

Zenodo (CERN European Organization for Nuclear Research)
Reduced inequalities
Openalex Percentile: Top 32%
Survey Methodology and Nonresponse
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