Free Shipping on orders over $100 🚚

0

Your Cart is Empty

There are no items in your cart.

Continue Shopping


Terminology Explained

Individuals, institutions, or organisations that collaborate to conduct a study. They bring skills and resources to the research project, such as expertise in specific scientific areas, access to participant pools, or specialised equipment and facilities. We primarily work with partners with a mutual interest in the crossover between nutrition and neuroscience.

A placebo-controlled study is a type of clinical trial where the effect of a treatment is tested against a placebo which is an inactive, substance designed to resemble the treatment. Participants are randomly assigned to a treatment group or a placebo group. This setup helps to determine if the observed effects are due to the treatment itself or other factors like participant expectation.

In a double-blind study, neither the participants nor the researchers know who is receiving the active treatment and who is receiving the placebo. This method is used to prevent bias in the results, as the expectations of the researchers and the participants could potentially influence the outcomes of the study.

The length of trial periods in a study refers to the duration over which the participants are observed while receiving the treatment or placebo. The trial period must be long enough to observe the intended effects or side effects of the treatment, and it can vary from a few minutes to several years, depending on what is being studied. Acute or chronic effects are of interest.

The number of participants, or sample size, in a study refers to the total number of individuals involved. Researchers choose the sample size based on the expected effects they aim to detect and the statistical power needed. Larger sample sizes generally provide more reliable results. The choice of who participates can be based on specific inclusion criteria relevant to the study’s aims.


the significance of their results. It represents the probability or the confidence we can have in the hypotheses . Typically, a p-value greater than 0.05 means we accept the null hypothesis (no effect) and below 0.05 means we can reject the null hypothesis, as there is a less than 5% chance the effect we see is due to chance.

Statistical significance is used to determine if the results of a study are likely to be true and not due to random chance. If a result is statistically significant, it means the likelihood that the observed effect is due to the treatment being high, based on the p-value. Researchers typically set a threshold before the study, often at a p-value of 0.05, to decide what level of significance they will accept.