Funding bias, also known as sponsorship bias, funding outcome bias, funding publication bias, and funding effect, refers to the tendency of a scientific study to support the interests of the study's financial sponsor. This phenomenon is recognized sufficiently that researchers undertake studies to examine bias in past published studies. Funding bias has been associated, in particular, with research into chemical toxicity, tobacco, and pharmaceutical drugs.[1] It is an instance of experimenter's bias.


Human nature

The psychology text Influence: Science and Practice describes the act of reciprocity as a trait in which a person feels obliged to return favors. This trait is embodied in all human cultures. Human nature may influence even the most ethical researchers to be affected by their sponsors, although they may genuinely deny it.[2]


Main article: scientific misconduct

Scientific malpractice involving shoddy research or data manipulation does occur in rare instances. Often, however, the quality of manufacturers' studies are at least as good as studies that were not funded by a special interest.[3] Therefore, bias usually occurs for other reasons.

Predetermined conclusion

Research results can be selected or discarded to support a predetermined conclusion.[4] The tobacco industry, for example, would publish their own internal research that invariably found minimal adverse health effects of passive smoking.[3]

A company that hires researchers to perform a study may require the researchers to sign a nondisclosure agreement before they are funded, by which researchers waive their right to release any results independently and release them only to the sponsor. The sponsor may fund several studies at the same time, suppressing results found contrary to their business interests while publicizing the results that support their interests. Indeed, a review of pharmaceutical studies revealed that research funded by drug companies was less likely to be published, but the drug-company-funded research that was published was more likely to report outcomes favorable to the sponsor.[5]

A double-blind study with only objective measures is less likely to be biased to support a given conclusion. However, the researchers or the sponsors still have opportunities to skew the results by discarding or ignoring undesirable data, qualitatively characterizing the results, and ultimately deciding whether to publish at all. Also, not all studies are possible to conduct double-blind.

Publication bias

Main article: publication bias

Scientist researcher Anders Sandberg writes that funding bias may be a form of publication bias. Because it is easier to publish positive results than inconclusive or no results, positive results may be correlated with being positive for the sponsor.[6]

Outcome reporting bias is related to publication bias and selection bias, in which multiple outcomes are measured but only the significant outcomes are reported, while insignificant or unfavorable outcomes are ignored.[7]

Selection of subjects or comparators

Main article: selection bias

Selection bias may result in a non-representative population of test subjects in spite of best efforts to obtain a representative sample. Even a double-blind study may be subject to biased selection of dependent variables, population (via inclusion and exclusion criteria), sample size, statistical methods, or inappropriate comparators, any of which can bias the outcome of a study to favor a particular conclusion.[5]


See also


  1. ^ Krimsky Sheldon (2013). "Do Financial Conflicts of Interest Bias Research? An Inquiry into the "Funding Effect" Hypothesis" (PDF). Science, Technology, & Human Values. 38 (4): 566–587. doi:10.1177/0162243912456271. S2CID 42598982. Archived from the original (PDF) on 2012-10-17. Retrieved 2015-09-15.
  2. ^ Cialdini, Robert B (2008-08-08). Influence: Science and Practice (5th ed). Prentice Hall. ISBN 978-0-205-60999-4.
  3. ^ a b c David Michaels (2008-07-15). "It's Not the Answers That Are Biased, It's the Questions". The Washington Post.
  4. ^ Wilmshurst, Peter (2007). "Dishonesty in Medical Research" (PDF). The Medico-Legal Journal. 75 (Pt 1): 3–12. doi:10.1258/rsmmlj.75.1.3. PMID 17506338. S2CID 26915448. Archived from the original (PDF) on 2013-05-21.
  5. ^ a b Lexchin, Joel; Bero, Lisa A; Djulbegovic, Benjamin; Clark, Otavio (2003-05-31). "Pharmaceutical industry sponsorship and research outcome and quality: systematic review". BMJ. 326 (7400): 1167–1170. doi:10.1136/bmj.326.7400.1167. PMC 156458. PMID 12775614.
  6. ^ Anders Sandberg (2007-01-14). "Supping with the Devil". OvercomingBias.
  7. ^ "Types of Bias". Cochrane Bias Methods Group. 2009-06-19. Retrieved 2010-08-04.
  8. ^ Christina Turner; George J Spilich (1997). "Research into smoking or nicotine and human cognitive performance: does the source of funding make a difference?". Addiction. 92 (11): 1423–1426. doi:10.1111/j.1360-0443.1997.tb02863.x. PMID 9519485. Archived from the original on 2012-10-21.
  9. ^ C. Bruce Baker; Michael T. Johnsrud; M. Lynn Crismon; Robert A. Rosenheck; Scott W. Woods (2003). "Quantitative analysis of sponsorship bias in economic studies of antidepressants". The British Journal of Psychiatry. 183 (6): 498–506. doi:10.1192/bjp.183.6.498. PMID 14645020.
  10. ^ Becker-Brüser W (2010). "Research in the pharmaceutical industry cannot be objective". Z Evid Fortbild Qual Gesundhwes. 104 (3): 183–9. doi:10.1016/j.zefq.2010.03.003. PMID 20608245.
  11. ^ Anke Huss; Matthias Egger; Kerstin Hug; Karin Huwiler-Müntener; Martin Röösli (2006-09-15). "Source of Funding and Results of Studies of Health Effects of Mobile Phone Use: Systematic Review of Experimental Studies". Environmental Health Perspectives. 115 (1): 1–4. doi:10.1289/ehp.9149. PMC 1797826. PMID 17366811.
  12. ^ vom Saal FS, Myers JP (2008). "Bisphenol A and Risk of Metabolic Disorders". JAMA. 300 (11): 1353–5. doi:10.1001/jama.300.11.1353. PMID 18799451.
  13. ^ Stephen Daniells (2009-09-25). "Splenda study: Industry and academia respond".
  14. ^ Schillinger D, Tran J, Mangurian C, Kearns C (1 November 2016). "Do Sugar-Sweetened Beverages Cause Obesity and Diabetes? Industry and the Manufacture of Scientific Controversy". Ann Intern Med. 165 (12): 895–897. doi:10.7326/L16-0534. PMC 7883900. PMID 27802504. S2CID 207537905.((cite journal)): CS1 maint: uses authors parameter (link)
  15. ^ Melissa Healy (31 October 2016). "Does the soda industry manipulate research on sugary drinks' health effects?". The Los Angeles Times.
  16. ^ Lundh, Andreas; Lexchin, Joel; Mintzes, Barbara; Schroll, Jeppe B.; Bero, Lisa (16 Feb 2017). "Industry sponsorship and research outcome". The Cochrane Database of Systematic Reviews. 2017 (2): MR000033. doi:10.1002/14651858.MR000033.pub3. ISSN 1469-493X. PMC 8132492. PMID 28207928.