6,944
Views
49
CrossRef citations to date
0
Altmetric
Comment

A Quantitative Review of Performance Feedback in Organizational Settings (1998-2018)

, , , ORCID Icon & ORCID Icon
Pages 303-332 | Published online: 13 Oct 2020
 

ABSTRACT

Researchers have extensively studied performance feedback in the past 40 years. In organizational behavior management (OBM), feedback is a popular intervention component that can effectively increase and maintain performance across settings and target behaviors. The purpose of this meta-analysis is to update and extend the previous feedback literature reviews. This meta-analysis includes 96 applied performance feedback applications from 71 articles published in four journals between 1998–2018. We coded each feedback application for application characteristics, feedback characteristics, and rigor of methodology. We evaluated each application’s effectiveness by visual inspection and by calculated effect sizes. We conducted a meta-analysis for feedback overall and per feedback characteristics for all applications and for applications that used rigorous methodology by adhering to the What Works Clearinghouse (WWC) standards. The meta-analysis results showed that feedback is an effective intervention, consistently producing large and very large effect sizes. Some feedback characteristics produced larger effect sizes more reliably.

Acknowledgments

We would like to thank Dr. Rachel Tilka and her students for their help in the preparation phase of the review.

Disclosure statement

No potential conflict of interest was reported by the authors.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 485.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.