Many researchers remain tempted to draw causal conclusions from observational data despite acknowledging that mere association is not causation because causal inference is the ultimate goal of most biomedical research. To find out whether and how statements in study reports present confusing use of causal language (or lack thereof), Olarte Parra and colleagues examined abstracts of research papers published in The BMJ in 2018.
Of 151 selected research papers, 60 described eligible studies. Of these 60, the authors classified the causal language used as ‘consistently causal’ (13%), ‘suggests causal’ (35%), ‘inconsistent’ (20%) and ‘consistently not causal’(32%). The inconsistencies found in both submitted and published versions were mainly due to mismatches between objectives and conclusions.
The authors conclude that further guidance is necessary for authors on what constitutes a causal statement and how to justify or discuss assumptions involved. Based on the work presented in this article, the authors provide a list of expressions beyond the term ‘cause’ which may inspire a useful and more comprehensive compendium on causal language.