AI Article Synopsis

  • The paper emphasizes the importance of rigorous bias assessment in systematic reviews and explores modifications to existing risk of bias tools to include quasi-experimental designs.
  • It critically evaluates current bias assessment tools, identifying gaps in how they address the validity of nonrandomized studies.
  • The authors propose enhancements to these tools to better assess the internal validity of quasi-experiments that have unobservable biases.

Article Abstract

Objectives: Rigorous and transparent bias assessment is a core component of high-quality systematic reviews. We assess modifications to existing risk of bias approaches to incorporate rigorous quasi-experimental approaches with selection on unobservables. These are nonrandomized studies using design-based approaches to control for unobservable sources of confounding such as difference studies, instrumental variables, interrupted time series, natural experiments, and regression-discontinuity designs.

Study Design And Setting: We review existing risk of bias tools. Drawing on these tools, we present domains of bias and suggest directions for evaluation questions.

Results: The review suggests that existing risk of bias tools provide, to different degrees, incomplete transparent criteria to assess the validity of these designs. The paper then presents an approach to evaluating the internal validity of quasi-experiments with selection on unobservables.

Conclusion: We conclude that tools for nonrandomized studies of interventions need to be further developed to incorporate evaluation questions for quasi-experiments with selection on unobservables.

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Source
http://dx.doi.org/10.1016/j.jclinepi.2017.02.015DOI Listing

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