EBM Definitions
Summary of evidence-based medicine (EBM) definitions
Blinding and Double Blinding
External Validity
Internal Validity
Heterogeneity (of a Study)
Homogeneity (of a Study)
P-Value
Intention-to-Treat (ITT) Analysis
- ITT refers to analyzing study participants based on the group they were originally assigned, regardless of whether they completed the treatment or adhered to the protocol.
- This preserves the benefits of randomization and prevents bias, reflecting real-world treatment effectiveness.
Blinding and Double Blinding
- Blinding: Concealing treatment allocation from participants, researchers, or assessors to reduce bias.
- Double Blinding: Both participants and researchers (or assessors) are unaware of treatment allocation, minimizing placebo effects and observer bias.
External Validity
- Refers to how well the results of a study can be generalized to other populations, settings, or conditions beyond the study sample.
- High external validity means findings are applicable to real-world clinical practice.
Internal Validity
- The extent to which a study is well-designed and free from bias, ensuring that observed effects are due to the intervention rather than confounding factors.
- High internal validity indicates strong causal inferences can be made.
Heterogeneity (of a Study)
- Describes the degree of variation in study results, populations, interventions, or methodologies among included studies in a systematic review or meta-analysis.
- High heterogeneity suggests variability that may limit the ability to pool study results meaningfully.
Homogeneity (of a Study)
- The opposite of heterogeneity; indicates that study results, populations, interventions, or methodologies are similar across included studies.
- High homogeneity strengthens the reliability of pooled data in meta-analyses.
P-Value
- A statistical measure representing the probability that observed study results occurred by chance.
- Specifically a p-value is defined as the probability of obtaining results as extreme as (or more extreme than) those observed in the study, assuming the null hypothesis is true.
- Typically, a p-value <0.05 is considered statistically significant, suggesting that the observed difference is unlikely due to chance alone, and providing evidence against the null hypothesis.