Causal Evidence and Dispositions in Medicine and Public Health

Int J Environ Res Public Health. 2020 Mar 11;17(6):1813. doi: 10.3390/ijerph17061813.


Since the introduction of evidence-based medicine, there have been discussions about the epistemic primacy of randomised controlled trials (RCTs) for establishing causality in medicine and public health. A growing movement within philosophy of science calls instead for evidential pluralism: that we need more than one single method to investigate health outcomes. How should such evidential pluralism look in practice? How useful are the various methods available for causal inquiry? Further, how should different types of causal evidence be evaluated? This paper proposes a constructive answer and introduces a framework aimed at supporting scientists in developing appropriate methodological approaches for exploring causality. We start from the philosophical tradition that highlights intrinsic properties (dispositions, causal powers or capacities) as essential features of causality. This abstract idea has wide methodological implications. The paper explains how different methods, such as lab experiments, case studies, N-of-1 trials, case control studies, cohort studies, RCTs and patient narratives, all have some strengths and some limitations for picking out intrinsic causal properties. We explain why considering philosophy of causality is crucial for evaluating causality in the health sciences. In our proposal, we combine the various methods in a temporal process, which could then take us from an observed phenomenon (e.g., a correlation) to a causal hypothesis and, finally, to improved theoretical knowledge.

Keywords: causality; dispositions; evidential pluralism; health outcomes; medicine; pharmacovigilance; predictions; public health; research methods.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Causality*
  • Evidence-Based Medicine*
  • Humans
  • Knowledge
  • Public Health*
  • Randomized Controlled Trials as Topic
  • Research Design