Ethics in Medicine

More on Doctored Images in Research Studies

Kristen Sparrow • October 29, 2022

To follow up on the blog post about the doctored images in a landmark study on Alzheimer’s, this article   Is written by a scientist who took it upon herself to look through thousands of journal articles in search of photoshopped and altered images.

The Times attempted to contact the lead scientists of the retracted papers with images reprinted in this essay. Only one responded; the others did not write back or declined to comment. The author who responded, Thomas J. Webster, said publishing the images had been an honest mistake.

Of course, the images themselves don’t directly reveal how they came into being or which authors were involved in making them. Although some duplicated images appear to be the result of intentional editing, it is possible that others are created from sloppy lab work, accidental mislabeling or miscommunication between colleagues.

Science needs to get serious about research fraud. Journals should be much faster at retracting papers containing photoshopped images or manipulated data — and should not publish them in the first place. Scientists who find flaws in published results should not be threatened with lawsuits in an attempt to silence criticism.

Here is a list of things I believe must change:

Journals must carry out better quality control. Publishers should hire image analysts and statistical experts to screen accepted papers before publication.

Journals need to act much faster — for example, within six months — when evidence of image manipulation arises.

We need national and international science integrity organizations that can independently investigate suspected cases of fraud and have some ability to punish the guilty.

Legitimate criticism of scientific research should receive legal protection.

Journals should pay the data detectives who find fatal errors or misconduct in published papers, similar to how tech companies pay bounties to computer security experts who find bugs in software.

As it becomes harder to distinguish between fake and real data, science might need to move toward a model based on reproduction, where Ph.D. students earn credit for replicating published studies, while the researchers whose work is reproduced get credit as well.

Despite all these problems, I believe in science. Firmly. We need trustworthy science to help us deal with consequential issues like climate change and pandemics. But science needs to be quicker and better at correcting itself.