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Inconsistent consistency: evaluating the well-defined intervention assumption in applied epidemiological research.

Jerzy Eisenberg-Guyot1, Katrina L Kezios2, Seth J Prins2,3

  • 1Division of Epidemiology, NYU Grossman School of Medicine, New York, NY, USA.

International Journal of Epidemiology
|March 4, 2025
PubMed
Summary
This summary is machine-generated.

Researchers rarely specify well-defined interventions when estimating causal effects using g-methods or targeted maximum likelihood estimation (TMLE). This review highlights significant gaps in applying causal inference assumptions in epidemiological studies.

Keywords:
Consistencycausal inferencepotential outcomesstable unit treatment value assumptiontreatment variation irrelevancewell-defined intervention

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Area of Science:

  • Epidemiology
  • Causal Inference
  • Health Research Methods

Background:

  • Textbook guidance emphasizes the well-defined intervention assumption for causal effect estimation.
  • Systematic evaluations of how this assumption is addressed in research are lacking.
  • This study examines the interpretation and application of the well-defined intervention assumption in epidemiological research using g-methods or targeted maximum likelihood estimation (TMLE).

Purpose of the Study:

  • To systematically review how researchers using g-methods or TMLE interpret and address the well-defined intervention assumption in observational epidemiological studies.
  • To assess the extent to which studies specify well-defined interventions and discuss key causal inference assumptions.

Main Methods:

  • Review of observational epidemiological studies published between 2000-2021 in top-impact epidemiology journals.
  • Assessment of whether authors aimed to estimate hypothetical intervention effects.
  • Evaluation of the discussion and specification of causal inference assumptions, including consistency and well-defined interventions.

Main Results:

  • Only 20% of studies aimed to estimate hypothetical intervention effects.
  • Almost no studies (1/29) specified 'how' an exposure would be intervened upon.
  • 64% of studies where the 'how' was not stated had implications for consistency (treatment variation irrelevance).
  • While 79% mentioned consistency, only 45% interpreted findings as hypothetical intervention effects.
  • Just 38% of intervention-effect studies featured well-defined interventions.

Conclusions:

  • Substantial discrepancies exist between guidelines for the well-defined intervention assumption and its application in research.
  • Authors of intervention-effect studies infrequently critically examine the validity of the well-defined intervention assumption.
  • There is a need for improved specification and critical evaluation of well-defined interventions in epidemiological research.