How Examine calculates evidence grades

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The Examine Database almost exclusively uses randomized controlled trials and meta-analyses of randomized controlled trials to maximize the likelihood of inferring causality from the data.

Interventions indexed in the Examine Database are assigned a letter grade from A to F, with A being the most effective and F being unsafe. Examine grades are automatically calculated from three main inputs:

  • Magnitude of effect
  • Consistency of effect across studies
  • The number of studies

Effect magnitudes are entered by hand by our expert research team. Examine researchers look at the body of evidence rather than single trials. They assess the magnitude of effect for any intervention studied for a specific outcome and take into account both the absolute magnitude and clinical significance to determine whether the effect is a small, medium, or large increase or decrease, or no effect.

Consistency scores are automatically calculated by comparing how well the effect directions line up between different studies in the Examine Database.

Letter grades correspond to general efficacy:

  • A: Multiple, mostly consistent studies suggest at least a moderate effect.
  • B–C: Fewer studies suggest a possible effect, there’s some inconsistency in the data, or the effect is small.
  • D: Either there’s very little research on the topic, the studies are highly inconsistent, the effect is null or very small, or a combination of these issues.
  • F: The evidence indicates the intervention may cause harm and should be avoided.