Data integrity, reliability and fraud in medical research.
BACKGROUND
Data reliability in original research requires collective trust from the academic community. Standards exist to ensure data integrity, but these safeguards are applied non-uniformly so errors or even fraud may still exist in the literature.


OBJECTIVE
To examine the prevalence and consequences of data errors, data reliability safeguards and fraudulent data among medical academics.


METHODS
Corresponding authors of every fourth primary research paper published in the Journal of the American Medical Association (2001-2003), Canadian Medical Association Journal (2001-2003), British Medical Journal (1998-2000), and Lancet (1998-2000) were surveyed electronically. Questions focused on each author's personal experience with data reliability, data errors and data interpretation.


RESULTS
Sixty-five percent (127/195) of corresponding authors responded. Ninety-four percent of respondents accepted full responsibility for the integrity of the last manuscript on which they were listed as co-author; however, 21% had discovered incorrect data after publication in previous manuscripts they had co-authored. Fraudulent data was discovered by 4% of respondents in their previous work. Four percent also noted 'smudged' data. Eighty-seven percent of respondents used data reliability safeguards in their last published manuscript, typically data review by multiple authors or double data entry. Twenty-one percent were involved in a paper that was submitted despite disagreement about the interpretation of the results, although the disagreeing author commonly withdrew from authorship.


CONCLUSIONS
Data reliability remains a difficult issue in medical literature. A significant proportion of respondents did not use data reliability safeguards. Research fraud does exist in academia; however, it was not reported to be highly prevalent.
Baerlocher
Mark Otto
MO
University of Toronto Radiology Residency Program, Toronto, Ontario, 13 Marshview Drive, Sackville, New Brunswick, Canada E4L 3B2. mark.baerlocher@utoronto.ca
O'Brien
Jeremy
J
Newton
Marshall
M
Gautam
Tina
T
Noble
Jason
J
D001319:Authorship; D035843:Biomedical Research / Q000592:standards* / Q000706:statistics & numerical data; D003625:Data Collection; D003627:Data Interpretation, Statistical; D010506:Periodicals as Topic / Q000592:standards / Q000706:statistics & numerical data; D015995:Prevalence; D015203:Reproducibility of Results; D012107:Research Design / Q000592:standards; D015871:Scientific Misconduct / Q000706:statistics & numerical data*