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Criterion Validity of Cognitive Reflection for Predicting Job Performance and Training Proficiency: A Meta-Analysis.

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Summary
This summary is machine-generated.

Cognitive reflection (CR) effectively predicts job performance and training success. While CR offers a small added benefit over cognitive intelligence for job performance, its predictive power for training proficiency is minimal.

Keywords:
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Area of Science:

  • Psychology
  • Industrial-Organizational Psychology
  • Human Resources

Background:

  • Cognitive reflection (CR) is increasingly recognized as a factor in decision-making.
  • Its predictive utility for occupational criteria requires further investigation.
  • Understanding the added value of CR over cognitive intelligence (CI) is crucial for personnel selection.

Purpose of the Study:

  • To conduct a meta-analysis on the validity of CR for predicting job performance and training proficiency.
  • To examine the incremental validity of CR over CI for these criteria.
  • To explore potential moderators of CR validity.

Main Methods:

  • A meta-analysis was performed on existing studies examining the relationship between CR and occupational outcomes.
  • Statistical methods were used to synthesize findings and calculate true validity.
  • Incremental validity analyses were conducted to assess the unique contribution of CR beyond CI.

Main Results:

  • CR demonstrated strong predictive validity for both job performance and training proficiency.
  • The validity of CR was consistent across different types of CR measures.
  • CR provided a small, statistically significant incremental validity over CI for job performance.
  • CR showed negligible incremental validity over CI for training proficiency.

Conclusions:

  • CR is a valuable predictor in personnel selection, demonstrating robust validity for job performance and training.
  • While CR offers some unique predictive variance for job performance, its incremental contribution over CI is modest.
  • The findings suggest that CR should be considered in selection processes, particularly for roles emphasizing complex decision-making, but its added value for training prediction is limited.