From Claim to Brain: A Public and Patient Involvement and Engagement Project on how Causal Language is interpreted in Healthcare Studies

Abstract Clear communication of evidence is central to healthcare decision-making and public trust in epidemiology. However, prior work suggests that members of the public may interpret causal and correlative language differently from researchers. We conducted two public and patient involvement and engagement activities to explore how non-researchers interpret causal and correlative claims in epidemiology. An online questionnaire (n=72) assessed interpretations of commonly used causal (“X causes Y”) and correlative (“X is associated with Y”) claims, while a follow-up focus group (n=4) explored reasoning, assumptions, and interpretations in greater depth. Participant interpretations frequently diverged from standard researcher interpretations. Causal language was consistently understood as indicating strong, well-established evidence and an underlying biological mechanism, while correlative language was perceived as tentative evidence for a causal relationship. Across activities, participants emphasised that conventional distinctions between causation and correlation may not function as intended for lay audiences, instead serving as a potential source of miscommunication. To better communicate evidence strength and clinical relevance, epidemiologists should look to adopt more audience-informed language and co-developed guidance.

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Publication Details

Journal
AJE Advances Research in Epidemiology
Published
2026-11-02
DOI
https://doi.org/10.1093/ajeadv/uuag042
Primary Topic
Health Literacy and Information Accessibility
Type
article
Field-Weighted Citation Impact
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article

From Claim to Brain: A Public and Patient Involvement and Engagement Project on how Causal Language is interpreted in Healthcare Studies

Emily Bassett, Amy M. Mason, Stephen Burgess
AJE Advances Research in Epidemiology
Health Literacy and Information Accessibility
article

From Claim to Brain: A Public and Patient Involvement and Engagement Project on how Causal Language is interpreted in Healthcare Studies

Emily Bassett, Amy M. Mason, Stephen Burgess
article en

Abstract

Abstract Clear communication of evidence is central to healthcare decision-making and public trust in epidemiology. However, prior work suggests that members of the public may interpret causal and correlative language differently from researchers. We conducted two public and patient involvement and engagement activities to explore how non-researchers interpret causal and correlative claims in epidemiology. An online questionnaire (n=72) assessed interpretations of commonly used causal (“X causes Y”) and correlative (“X is associated with Y”) claims, while a follow-up focus group (n=4) explored reasoning, assumptions, and interpretations in greater depth. Participant interpretations frequently diverged from standard researcher interpretations. Causal language was consistently understood as indicating strong, well-established evidence and an underlying biological mechanism, while correlative language was perceived as tentative evidence for a causal relationship. Across activities, participants emphasised that conventional distinctions between causation and correlation may not function as intended for lay audiences, instead serving as a potential source of miscommunication. To better communicate evidence strength and clinical relevance, epidemiologists should look to adopt more audience-informed language and co-developed guidance.

AJE Advances Research in Epidemiology
University of Cambridge (GB), British Heart Foundation (GB), MRC Biostatistics Unit (GB)
Good health and well-being
Openalex Percentile: Top 10%
Health Literacy and Information Accessibility
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