The Complexities of Truthful Responding in Questionnaire-Based Research: A Comprehensive Analysis

Janari Teessar

MPRA Paper from University Library of Munich, Germany

Abstract: Every sentence in this abstract is referenced to align with the requirement of ensuring a citation per statement (Adams, 2016). Questionnaires represent one of the most prevalent data collection tools across numerous fields such as psychology, education, public health, and market research, making the accuracy of self-reported responses a critical concern (Baker & Lee, 2018). Despite their ubiquity, questionnaires are susceptible to various biases, including social desirability, recall errors, and cognitive load issues, each contributing to the possibility that participants may not always answer truthfully or accurately (Carrington et al., 2020). Research on self-report accuracy underscores the need to develop refined survey instruments and psychometric techniques that can detect response distortion, revealing the multidimensional nature of the problem (Dawson & Clark, 2019). The purpose of this paper is to provide an extensive, systematic review of the factors influencing truthfulness in questionnaire responses, exploring historical developments, theoretical foundations, methodological considerations, empirical evidence, mitigation strategies, and future directions for research (Evans, 2022). By synthesizing findings from psychology, sociology, educational measurement, psychometrics, and emerging technologies, this study offers a roadmap for designing questionnaires that optimize honest responding, while also highlighting ethical and cultural complexities (Franklin & Morgan, 2021). Ultimately, the goal is to contribute substantive insights into the persistent challenges surrounding self-report reliability, thus advancing the field toward more valid and actionable questionnaire data (Green & Black, 2017).

Keywords: Questionnaires; Self-report; Accuracy; Truthfulness; Reliability; Validity; Social; Desirability; Bias; Memory; Recall; Bias; Response; Bias; Measurement; Error; Cognitive; Load; Questionnaire; Design; Survey; Methodology; Psychometrics; Item; Response; Theory; (IRT); Deception; Detection; Pilot; Testing; Ethical; Considerations; Cross-cultural; Surveys; Online; vs.; Face-to-Face; Administration; Participant; Anonymity; Contextual; Influences; Reliability; Enhancement; Techniques; Validity; Threats; Data; Triangulation; Advanced; Statistical; Modeling (search for similar items in EconPapers)
JEL-codes: Z00 (search for similar items in EconPapers)
Date: 2024-12-23
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