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Barriers to Adopting Evidence From Bayesian Adaptive Clinical Trials in Critical Care: A Randomized Experiment With

Brian E Malley¹, Joel M Levin¹, Jeremy M Kahn¹

¹Center for Research, Investigation, and Systems Modeling of Acute Illness (B. E. M., J. M. K., L. A. B., and D. T. H.), Department of Critical Care Medicine, the Joseph M. Katz Graduate School of Business (J. M. L.), University of Pittsburgh, Pittsburgh, PA; the Department of Emergency Medicine (B. E. M.), Maine Medical Center, Portland, ME; and the Rady School of Management (J. M. L.), University of California, San Diego, San Diego, CA.

CHEST Critical Care

|June 26, 2026

Abstract

Background:

Randomized clinical trials are a mainstay of medical research, but have drawbacks including time and cost. Bayesian adaptive trials can improve the speed and efficiency of clinical trials and are an increasingly common trial design in critical care. However, the complexity of Bayesian adaptive trials may prevent clinicians from easily interpreting their results.

Research Question:

Do intensivist physicians perceive, understand, and accept results from Bayesian adaptive clinical trials differently than results from traditional frequentist trials when presented with otherwise identical data?

Study Design And Methods:

We surveyed US intensivists from March through April 2022 about their perceptions of Bayesian adaptive trials. Within the survey, participants were randomized to read an abstract for a hypothetical new sepsis drug trial that used either Bayesian adaptive methods or traditional frequentist methods, with both abstracts based on the same simulated trial data. Participants then were asked about perceived understanding, validity, and general acceptance of the trial's methods and results. Survey responses were compared between experimental groups using Mann-Whitney U tests and ordinal logistic regressions.

Results:

We received complete results from 273 of 592 eligible physicians (response rate, 46.1%). Participants in the Bayesian group reported lesser understanding of the methods (mean rating in frequentist vs Bayesian groups, 3.18 vs 2.85; P < .001) and the results of the trial (mean rating, 3.36 vs 3.00; P < .001) compared with the frequentist group. Participants in the Bayesian group also expressed greater concerns about trial validity (eg, mean rating about the risk of type 1 error, 2.70 vs 2.99; P = .001) compared with the frequentist group. Participants in both groups reported similar beliefs about acceptance of trial results (eg, mean rating in frequentist vs Bayesian group about the effectiveness of the study drug, 3.87 vs 3.86; P = .47).

Interpretation:

Our results show that despite lower perceived understanding of Bayesian trials and skepticism about elements of their validity, no substantive differences were found in intensivist physician acceptance of Bayesian trial results compared with frequentist trial results. CHEST Critical Care 2026; 4(2):100264.

Keywords:

Bayesian statistics clinical trials critical care frequentist statistics implementation science intensive care sepsis survey methods

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