Times are changing, bias isn't: a meta-meta-analysis on publication bias detection practices, prevalence rates, and predictors in industrial/organizational psychology

Magdalena Siegel, Junia Sophia Nur Eder, Jelte M. Wicherts, Jakob Pietschnig

Research output: Contribution to journalA1: Web of Science-article

Abstract

Effect misestimations plague Psychological Science, but advances in the identification of dissemination biases in general and publication bias in particular have helped in dealing with biased effects in the literature. However, the application of publication bias detection methods appears to be not equally prevalent across subdisciplines. It has been suggested that particularly in I/O Psychology, appropriate publication bias detection methods are underused. In this meta-meta-analysis, we present prevalence estimates, predictors, and time trends of publication bias in 128 meta-analyses that were published in the Journal of Applied Psychology (7,263 effect sizes, 3,000,000+ participants). Moreover, we reanalyzed data of 87 meta-analyses and applied nine standard and more modern publication bias detection methods. We show that (a) the bias detection method applications are underused (only 41% of meta-analyses use at least one method) but have increased in recent years, (b) those meta-analyses that apply such methods now use more, but mostly inappropriate methods, and (c) the prevalence of potential publication bias is concerning but mostly remains undetected. Although our results indicate somewhat of a trend toward higher bias awareness, they substantiate concerns about potential publication bias in I/O Psychology, warranting increased researcher awareness about appropriate and state-of-the-art bias detection and triangulation. Embracing open science practices such as data sharing or study preregistration is needed to raise reproducibility and ultimately strengthen Psychological Science in general and I/O Psychology in particular.

Original languageEnglish
JournalJournal of Applied Psychology
Number of pages28
ISSN0021-9010
DOIs
Publication statusE-pub ahead of print - 2022

Keywords

  • dissemination bias
  • publication bias
  • meta-meta-analysis
  • industrial and organizational psychology
  • decline effect
  • WORK-FAMILY CONFLICT
  • COGNITIVE-ABILITY TESTS
  • MEMBER EXCHANGE LMX
  • FILE DRAWER PROBLEM
  • JOB-PERFORMANCE
  • METAANALYTIC EXAMINATION
  • 5-FACTOR MODEL
  • COMPREHENSIVE METAANALYSIS
  • ORGANIZATIONAL COMMITMENT
  • CONDUCTING METAANALYSES

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