When editors confuse direct criticism with rudeness, science loses – Retraction Watch

Jasmin Jamshidi-Naeini

In January 2022, motivated by our experience with eClinicalMedicine, we wrote about the mishandling of published errors by journal editors. We noticed that the methods used for the analysis of a cluster randomized trial published in the journal were invalid. Using a valid approach, we reanalyzed the raw data, which was shared with us by the original authors. The results of the trial were overturned.

As Retraction Watch readers may recall, we then submitted a manuscript describing why the original methods were invalid, what a valid analysis should be, and our results after performing a valid analysis. After a first refusal of office “in the light of [the journal’s] pipeline” and other correspondence, the journal shared our findings with the statistician involved in the original review and the original authors and asked for their responses.

After receiving the responses, both of which we believe contained factually incorrect statements, the editorial team eventually suggested that we summarize our full manuscript as a 1000-word letter to submit to the journal. We disagreed that a letter would allow us to fully communicate our methods and reanalysis. So, to respect the journal’s word limit while fully outlining our arguments, we published our additional points as a preprint and cited the preprint in a letter we submitted to the journal.

It was then that we encountered another obstacle to the correction of the literature.

Colby Vorland

We received the first review request from the editorial team with suggested edits followed by the wording of our letter. We were asked to remove any wording referring to the original analysis as “invalid” or “incorrect” and any wording referring to our reanalysis as “valid”, “correct” or “legitimate”. These edits minimized our reanalysis and the conclusions drawn (which overruled the results of the original analysis), referring instead to “a different interpretation (with a different analysis)”.

The editorial team had changed our core message about the inaccuracy of the original analysis and conclusions, and the accuracy of our reanalysis approach. The editorial team also removed citations to a link to additional information, where we had provided depth and clarity to interested readers, including our statistical code for reanalysis.

For two rounds, we tried to meet the expectations of the editorial team by partially accepting their suggested revisions and explaining why further revisions would change our intended message and were therefore unacceptable to us. Our responses were rejected and the editorial team requested the exact same revisions each time. This felt like an ultimatum to us: either publish with the revisions desired by the editorial team, or not publish the corrected results at all.

Although we didn’t agree with their changes, we were finally forced to accept them. The letter was finally published on October 6, 2022. The original article is uncorrected.

Andre Brown

This wasn’t the first time we’ve been asked to revise sentences like “analysis was incorrect” or “results were overruled using a valid analysis” into sentences like “an alternative analysis showed something of different”. Calling a “good alternative” analysis an “alternative” analysis does not make it clear to readers that the original analysis was demonstrably incorrect by any reasonable standard of statistical knowledge.

When we identify unequivocal errors in the published literature, we often point them out to journal editors. Some journal editors consider what we believe to be simply sharp, clear statements about the accuracy or lack of analyzes to be somehow rude, unfair, or as a reviewer of one of our manuscripts describes, ” unnecessarily pejorative”.

Certainly, there are cases of rude or worse behavior in science. Michael Lauer, NIH Deputy Director for Extramural Research, recently shared true stories about NIH staff and review board members facing “inappropriate and uncivil conduct” by candidates. Lauer’s examples involve using an aggressive tone, being condescending, or conducting abusive correspondence. All of these behaviors are rude, uncivil and unfair.

David Allison

However, there is nothing rude or unfair in saying that a particular analysis was incorrect, erroneous or invalid and therefore that the conclusions drawn from it are invalid or unfounded. Editors’ struggle to differentiate rudeness from frankness may in part be related to a notion we call “the second demarcation problem”: some editors find it difficult (or unwilling) to distinguish unequivocal errors from questions. subjective scientific opinion. The former need to be corrected, while the latter merit scientific debate.

On the other hand, those interested in critiquing public research to promote the rigor, reproducibility, transparency, and reliability of science sometimes interpret the encouragement to be polite and civil as an encouragement to keep quiet. .

Lilian Golzarri-Arroyo

But one can criticize professionally, politely, constructively, and as previously stated’directly‘ without being silent. We must not remain silent when we see flaws in the research literature. We must engage in dialogue and report the errors we detect. However, we should not allow the need not to be silenced in our critics to be a license for rudeness or personal attacks.

The clear distinction between errors and legitimate scientific debate should not be undermined by the pretense of politeness. Ignoring an unequivocal error by not acknowledging its inaccuracy or downgrading a valid reanalysis by calling it an alternative analysis gives the impression that the invalid approach can be considered correct. It corrupts the integrity and reliability of science.

There is no passive magical process by which science corrects itself into an anthropomorphized nebulous figure. Maintaining the self-correcting nature of science requires scientists to correct science from within the realm of science, and scientists can be polite, civil, constructive, and direct when they do so.

Jasmine Jamshidi-Naeini is a postdoctoral fellow and Colby J. Vorland is Scientific Research Assistantt at the Indiana University School of Public Health in Bloomington, where David B. Allison is dean and Lilian Golzarri-Arroyo is a biostatistician at the school’s Biostatistics Consulting Center. AAndrew W. Brown is an Associate Professor at the University of Arkansas for Medical Sciences.

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