Association Does Not Mean Causation, When Observational Data Were Misinterpreted as Causal: The Observational Interpretation Fallacy

Abstract

Background: The differentiation between association and causation is a significant challenge in medical research, often further complicated by cognitive biases that erroneously interpret coincidental observational data as indicative of causality. Such misinterpretations can lead to misguided clinical guidelines and healthcare practice, potentially endangering patient safety and leading to inefficient use of resources.

Methods: We conducted an extensive search of PubMed, Cochrane, and Embase databases up to March 2024, identifying circumstances where associations from observational studies were incorrectly deemed causal. These instances led to changes in clinical practice, embodying what we have termed the 'observational interpretation fallacy'.

Results: Our search identified 16 notable cases where observational study-derived associations, initially thought to influence clinical practices and guidelines positively, were later contradicted by findings from randomised controlled trials or further studies, necessitating significant revisions in clinical practice.

Conclusion: In many cases, misinterpretation of observational finding negatively affecting patient care and public health policies. Addressing and rectifying the observational interpretation fallacy is crucial for the progression of medical research and the maintenance of safe and effective clinical practice. It is imperative for health policymakers, clinicians, and the lay public to critically assess research outcomes and make health-related decisions based on a foundation of evidence-based medicine. This approach ensures the alignment of medical practices with the most current and robust scientific evidence, safeguarding patient welfare and optimising resource allocation.

Keywords: association; causation; observational interpretation fallacy; observational studies; randomised controlled trial.