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Causal and Associational Language in Observational Health Research: A Systematic Evaluation.

Authors :
Haber NA
Wieten SE
Rohrer JM
Arah OA
Tennant PWG
Stuart EA
Murray EJ
Pilleron S
Lam ST
Riederer E
Howcutt SJ
Simmons AE
Leyrat C
Schoenegger P
Booman A
Dufour MK
O'Donoghue AL
Baglini R
Do S
Takashima MR
Evans TR
Rodriguez-Molina D
Alsalti TM
Dunleavy DJ
Meyerowitz-Katz G
Antonietti A
Calvache JA
Kelson MJ
Salvia MG
Parra CO
Khalatbari-Soltani S
McLinden T
Chatton A
Seiler J
Steriu A
Alshihayb TS
Twardowski SE
Dabravolskaj J
Au E
Hoopsick RA
Suresh S
Judd N
Peña S
Axfors C
Khan P
Rivera Aguirre AE
Odo NU
Schmid I
Fox MP
Source :
American journal of epidemiology [Am J Epidemiol] 2022 Nov 19; Vol. 191 (12), pp. 2084-2097.
Publication Year :
2022

Abstract

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. We searched for and screened 1,170 articles from 18 high-profile journals (65 per journal) published from 2010-2019. 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. 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. This research undercuts the assumption that avoiding "causal" words leads to clarity of interpretation in medical research.<br /> (© The Author(s) 2022. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Details

Language :
English
ISSN :
1476-6256
Volume :
191
Issue :
12
Database :
MEDLINE
Journal :
American journal of epidemiology
Publication Type :
Academic Journal
Accession number :
35925053
Full Text :
https://doi.org/10.1093/aje/kwac137