Background: Health sciences research often explores the association between exposure and outcome, aiming to infer causal effects even with nonrandom assignment. While caution is advised due to complexities, some guidelines prohibit causal language outside of randomized controlled trials. Researchers and editors resort to euphemisms or partial use of causal language to maintain clarity and plausibility. However, there is ambiguity in defining causal language without established standards or categorizations, and this leads to potential disconnects between the authors’ intentions, methods, conclusions, and the perceptions of the work by research consumers and decision-makers.

Objectives: We estimated the degree to which language used in the high-profile medical/public health/epidemiology literature implied causality using language linking exposures to outcomes and action recommendations; examined disconnects between language and recommendations; identified the most common linking phrases; and estimated how strongly linking phrases imply causality.

Methods: We searched for and screened 1170 articles from 18 high-profile journals (65 per journal) published from 2010 to 2019. Based on written framing and systematic guidance, 3
reviewers rated the degree of causality implied in abstracts and full text for exposure/outcome linking language and action recommendations.

Results: Reviewers rated the causal implication of exposure/outcome linking language as none (no causal implication) in 13.8%, weak in 34.2%, moderate in 33.2%, and strong in 18.7% of abstracts. The implied causality of action recommendations was higher than the implied causality of linking sentences for 44.5% or commensurate for 40.3% of articles. The most common linking word in abstracts was “associate” (45.7%). Reviewers’ ratings of linking word roots were highly heterogeneous; over half of reviewers rated “association” as having at least some causal implication.

Conclusions: This research undercuts the assumption that avoiding “causal” words leads to clarity of interpretation in medical research. Failure to align research questions with actionable implications can lead to confusion. This misalignment, coupled with the omission of causal inference in research, can weaken methodological accountability. Rather than focusing on specific words, researchers, consumers, and reviewers should prioritize identifying and assessing causal inference study designs and assumptions.

There was no involvement of public or consumers.
The full author list is in additional information.