Research Fraud: Falsification and Fabrication in Research Data

Although uncommon, it’s not unheard of that researchers are accused of falsifying and/or fabrication research. In addition to other malintent, like plagiarism, duplication in publishing or multiple submissions. The tricky part is finding and identifying true fraudulent activity, even through peer review processes. Even highly regarded journals have accepted articles that are suspected of research fraud. On the other hand, some researchers have had their careers and reputations compromised by false accusations. Even if the false accusation was cleared, intense media coverage on the accusation versus the acquittal can mean permanent damage to the researcher.

What is the difference between falsification and fabrication?

Any type of research fraud usually involves publishing conclusions, or even data, that were either made up or changed. There are two different types of research fraud; fabrication and falsification. Obviously, they are related. However, they are distinctly different.

Falsification essentially involves manipulating or changing data, research materials, processes, equipment and, of course, results. This can include altering data or results in a way where the research is not accurate. For example, a researcher might be looking for a particular outcome, and the actual research did not support their theory. They might manipulate the data or analysis to match the research to the desired results.

Fabrication, on the other hand, is more about making up research results and data, and reporting them as true. This can happen when a researcher, for example, states that a particular lab process was done when, in fact, it wasn’t. Or that the research didn’t take place at all, in the case of a study results from previous research were copied and published as original research.

Obviously, both falsification and fabrication of data and research are extremely serious forms of misconduct. Primarily because they can result in an inaccurate scientific record that does not reflect scientific truth. Additionally, research fraud deceives important stakeholders of the research, like sponsoring institutions, funders, employers, the readers of the research and the general public.

How to Detect Fabricated Data

Sometimes it’s easy to identify fraud and fabricated research. Maybe, for example, an evaluator of the research is aware that a particular lab doesn’t have the capability to conduct a particular form of research, contrary to the claims of the researcher. Or, data from the control experiment may be presented as too “perfect,” leading to suspicions of fabricated data.

Suspected data manipulation in research, fabrication or falsification is subject to reporting and investigation to determine if the intent was to commit fraud, or if it was a mistake or oversight. Most publishers have extremely strict policies about manipulation of images, as well as demanding access to the researcher’s data.

Image Manipulation in Research

Another fairly common fabrication relates to images that appear to have been manipulated. It should be noted that image enhancement is often acceptable, however any enhancement must relate to the actual data, and whatever image results from the enhancement must accurately represent the data. If an image is significantly manipulated, it must be disclosed in the figure caption and/or your “materials and methods” section of the manuscript.

So, the bottom line is that image manipulation in research is okay, as long as the manipulation is to improve clarity, no specific features are introduced, removed, moved, obscured or enhanced. Minor adjustments to brightness, color balance and contrast are acceptable if they don’t eliminate or obscure information that is present in the original image.

Protecting Your Reputation

A researcher’s worst nightmare might be the accusation of committing fraud. Of course, unintentional errors do happen, and unfortunately they can appear to be misconduct. However, it should be made clear that an honest error is not considered research misconduct.

To avoid any false accusations, make sure your research is 100% accurate and any methods and processes are expressed accurately. Ensure that any images that might be enhanced are noted as such, and include the original image with your submission. Keep records of all raw data; if falsification or fabrication are suspected, the journal or other investigative body will demand to review your information. Therefore, flawless records must be kept, analyzed and reported. Additionally, certain research topics, such as studies of human subjects, require a specific duration of data retention.

If you discover an accidental published error, follow the steps outlined in our article about retracting or withdrawing your research.

The Bottom Line

A researcher must take extra care to ensure that their data and research can not even be suspected of fraud via falsification and fabrication. You can do this by being transparent and honest about any and all research, data, analysis and conclusions. Remembering that the purpose of research is to further collective knowledge over supporting desired outcomes is key to ensuring integrity in research.

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