To: Science over language: a plea to consider language bias in scientific publishing
Rohan Magoon

Abstract
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Taxonomy
TopicsHIV/AIDS Impact and Responses
To the Editor
It has indeed been gratifying to have recently read an Editorial by González-Dambrauskas et al.: "Science over language: a plea to consider language bias in scientific publishing", which features at an opportune time to blow an all-important clarion call for Sticking to Science while publishing academic content in scientific journals.^(1)^ In harmony with the noble theme of the index Editorial, i.e., to preserve the health of our research ecosystem, it is believed that the addition of another relevant aspect in this topic would take the discussion further in the right direction.^(1–5)^
Delving deeper into the complex trinity of science, language, and research, it is noteworthy how Lazarus et al. bring the concept of linguistic spin to the fore.^(2)^ Meanwhile, spin, by itself, is characterized by ‘the manipulation of language to potentially mislead readers from the likely truth of the results’; the former research group outlines the utilization of a causal language to have featured as the most prevalent strategy of spin, in a considerable 53% of the abstracts assessed across 128 non-randomized interventional articles.^(2,3)^ Ahead of the matter, which is intertwined between reporting and interpretation, it has something to do with rhetorical additions to manipulate the readers. Interestingly, Lobo, having labeled spin to involve altering the very presentation of facts aided by "disingenuous, deceptive, and manipulative tactics", highlights the larger problem spin may cause when employed in the positive randomized controlled trials providing a base for formulating the clinical care recommendations.^(4)^
Simultaneously, in the specific context of language barriers discussed by González-Dambrauskas et al., SPIN-Prediction Models (SPIN-PM, a consensus framework mapping spin practices) identify the language barriers to facilitate spin in the studies about prediction models, particularly in the background of inexperience and in the absence of requisite guidance.^(1,5)^
Acknowledging the present-day meaningfulness of the Editorial again, it is encouraging to witness serious discussions surrounding the subject of science beyond statistical significance.^(1)^
The reference list from the paper itself. Each links out to its DOI / PubMed record.
- 1González-Dambrauskas S Salluh JI Machado FR Rotta AT Science over language: a plea to consider language bias in scientific publishing Crit Care Sci 202436 e 20240084 en 10.62675/2965-2774.20240084-en PMC 1123920139046061 · doi ↗ · pubmed ↗
- 2Lazarus C Haneef R Ravaud P Boutron I Classification and prevalence of spin in abstracts of non-randomized studies evaluating an intervention BMC Med Res Methodol 201515185852646256510.1186/s 12874-015-0079-x PMC 4604617 · doi ↗ · pubmed ↗
- 3Magoon R Jose J Safeguarding anaesthesia research from spin Br J Anaesth 20201256 e 460e 4623295820410.1016/j.bja.2020.08.042 · doi ↗ · pubmed ↗
- 4Lobo DN Fragility, Spin, and Interpretation of Randomized Clinical Trials Crit Care Med 20194734864883076851110.1097/CCM.0000000000003604 · doi ↗ · pubmed ↗
- 5Andaur Navarro CL Damen JA Ghannad M Dhiman P van Smeden M Reitsma JB SPIN-PM: a consensus framework to evaluate the presence of spin in studies on prediction models J Clin Epidemiol 20241701113641113643863152910.1016/j.jclinepi.2024.111364 · doi ↗ · pubmed ↗
