Retractions in the Research Literature: Misconduct or Mistakes?

Med J Aust. 2006 Aug 7;185(3):152-4.


Objective: To determine how commonly articles are retracted on the basis of unintentional mistakes, and whether these articles differ from those retracted for scientific misconduct in authorship, funding, type of study, publication, and time to retraction.

Data source and study selection: All retractions of English language publications indexed in MEDLINE between 1982 and 2002 were extracted.

Data extraction: Two reviewers categorised the reasons for retraction of each article as misconduct (falsification, fabrication, or plagiarism) or unintentional error (mistakes in sampling, procedures, or data analysis; failure to reproduce findings; accidental omission of information about methods or data analysis).

Data synthesis: Of the 395 articles retracted between 1982 and 2002, 107 (27.1%) were retracted because of scientific misconduct, 244 (61.8%) because of unintentional errors, and 44 (11.1%) could not be categorised. Compared with articles retracted because of misconduct, articles with unintentional mistakes were more likely to have multiple authors, no reported funding source, and to be published in frequently cited journals. They were more likely to be retracted by the author(s) of the article, and the retraction was more likely to occur more promptly (mean, 2.0 years; 95% CI, 1.8-2.2) than articles withdrawn because of misconduct (mean, 3.3 years; 95% CI, 2.7-3.9) (P < 0.05 for all comparisons).

Conclusions: Retractions in the biomedical literature were more than twice as likely to result from unintentional mistakes than from scientific misconduct. The different characteristics of articles retracted for misconduct and for mistakes reflect distinct causes and, potentially, distinct solutions.

MeSH terms

  • Authorship
  • Bibliometrics*
  • Biomedical Research*
  • Humans
  • Periodicals as Topic / statistics & numerical data*
  • Research Design / statistics & numerical data*
  • Retraction of Publication as Topic*
  • Scientific Misconduct / statistics & numerical data*