New White Paper Provides Practical Advice for Combatting Threats to Data Quality

Insufficient effort responding (IER) on psychological assessments is a well-studied topic with far-reaching implications that stretch across many organizational domains. IER, unfortunately, threatens data quality in assessments of psychological and organizational topics. Researchers have, for instance, detected IER in various assessments, including low-stakes employee surveys, job analysis questionnaires, personality assessments, and ability tests.

In the latest SIOP White Paper, Insufficient Effort Responding to Psychological Assessments: Practical Advice for Combatting a Serious Threat to Data Quality, authors Nathan A. Bowling, Jason L. Huang, and Justin A. DeSimone review IER literature and provide practical advice that organizational practitioners and researchers can use to mitigate the effects of IER in their data.

According to the authors, “The science and practice of I-O psychology—as in other fields—depends on the availability of high-quality data. Our white paper provides actionable advice that researchers and practitioners can use to enhance data quality.”

In the paper, the authors go into detail on two IER mitigation strategies: detection and deletion of high-IER data and prevention of IER.

“Respondents to psychological assessments, unfortunately, often engage in IER,” the authors said. “Low-quality data yields untrustworthy findings. Ignoring IER undermines data quality and compromises the validity of data-driven insights. It is thus critical that researchers and practitioners take steps to mitigate IER.”

Ignoring IER poses high risk for unknowingly collecting low-quality data, which can lead to flawed conclusions and poor organizational decisions. This white paper describes a set of IER measures that are effective and easily employed within most data collection efforts. These measures help iden¬tify and potentially screen out inattentive participants, thereby improving data quality. Additionally, the authors suggest designing data collection efforts to mitigate IER. In doing so, organizational researchers and practitioners can be more confident in the quality of the data they collect, the analyses they conduct, the conclusions they draw, and the decisions they make.

“IER is a widespread problem that undermines data quality across various types of psychological assessments,” the authors said. “Fortunately, researchers have made considerable progress in the detection and prevention of IER. This white paper describes practical steps that can enhance data quality.”

For more important and timely topics in I-O psychology, visit the SIOP White Paper webpage for more white papers.