Study Guide
A short guide to the different types of studies and what they mean.
Study Types – What Do They Mean?
Not all studies are equally strong. The following hierarchy shows how reliable different study types are:
Multiple studies (often high-quality RCTs) on the same topic are pooled and statistically analyzed. This produces the most reliable overall result. A meta-analysis is the strongest form of evidence.
This is the strongest individual study type in humans. One group receives the supplement, another receives a placebo. Participants are randomly assigned and the study is often double-blind. RCTs provide the best evidence from a single study.
The researcher systematically searches all available studies and summarizes them. Very solid, but slightly weaker than a meta-analysis.
The effect is tested in living animals (e.g. rats or mice). Rats and mice are genetically surprisingly similar to humans (85–90% of genes have counterparts). The big advantage is absolute control over every aspect of life. Important for safety testing and initial findings, but less meaningful than human studies, as animals can react differently despite genetic similarities.
People are observed in everyday life, without an experiment. Interesting for initial clues, but not as conclusive as controlled studies.
Very small investigations with few participants. Important for new ideas, but not yet very meaningful.
Outcomes – Positive, Neutral or Negative?
On EvidenceBase we rate each study with one of three outcomes:
Tips for Interpretation
A single study does not directly prove anything – only multiple consistent results create a clear picture.
Always look at dosage, duration and target group – results are often not directly transferable.
Funding sources can influence results – look for independent studies.
Statistical significance ≠ clinical relevance. An effect can be significant but practically small.
Meta-analyses are only as good as their studies. Pay attention to heterogeneity (variability). Large differences in dosage, duration, participant age or study quality can strongly distort the overall result. Always look at the individual studies more closely.