Are Biasing Factors Idiosyncratic to Measures? A Comparison of Interpersonal Conflict, Organizational Constraints, and Workload

Paul E. Spector, Cheryl E. Gray, Christopher C. Rosen

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Widespread concern has been raised about the possibility of potential biasing factors influencing the measurement of organizational variables and distorting inferences and conclusions reached about them. Recent research calls for a measure-centric approach in which every measure is independently evaluated to assess what factor(s) may uniquely bias it. This paper examines three popular stressor measures from this perspective. Across three studies, we examine factors that may bias three popular measures of job stressors: The Interpersonal Conflict at Work Scale (ICAWS), the Organizational Constraints Scale (OCS), and the Quantitative Workload Inventory (QWI). The first study used a two-wave design to survey 276 MTurk workers to assess the three stressor scales, four strains, and five measures of potential bias sources: hostile attribution bias, negative affectivity, mood, neutral objects satisfaction, and social desirability. The second study used an experimental design with 439 MTurk workers who were randomly assigned to a positive, negative, or no mood induction condition to assess effects on means of the three stressor measures and their correlations with strains. The third study surveyed 161 employee-supervisor dyads to explore the convergence of results involving the three stressor measures across sources. Based on several forms of evidence we conclude that potential biasing factors affect the three stressor measures differently, supporting the merits of a measure centric approach, even among measures in the same domain.

Original languageEnglish
Pages (from-to)983-1002
Number of pages20
JournalJournal of Business and Psychology
Volume38
Issue number5
DOIs
StatePublished - Oct 2023

Keywords

  • Construct validity
  • Interpersonal conflict
  • Method variance
  • Organizational constraints
  • Stress
  • Workload

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