The thing being tested (like a new drug, device, or therapy). In this context, it’s the Ritual product being tested. Sometimes referred to as “the treatment”.

The group that does not get the treatment and is used for comparison. Depending on ethics, they may get an “active control,” which could be the standard treatment, another product on the market, or a placebo.

A “dummy treatment” (sometimes called a sugar pill) that has no real effect, used to see if the new treatment works better than nothing.

Assigning people by chance to different groups (treatment vs. control), to keep the study fair.

When participants and/or researchers don’t know who’s getting which treatment, to help avoid bias. Note: “Double blind” means that neither the participants nor the researchers know which treatment the participants are getting.

The process where participants are told all the details (risks, benefits, what to expect) before deciding to join.

The lead researcher responsible for running the study safely and correctly.

A U.S. government website that provides information on clinical studies being done around the world. You can search for trials by condition, treatment, or location.

A group of independent experts that reviews research studies to make sure they’re ethical and participants are protected.

When results of a study are unfairly influenced by the way it was designed, conducted, or interpreted, instead of showing the true effect.

A number that helps show whether the results of a study are likely real or could have happened by chance. A smaller p-value (like < 0.05) usually means the result is considered “statistically significant.”

Indicates the study results are unlikely to have occurred by chance alone (often when p < 0.05), but it doesn’t mean the effect is large or important.

The likelihood that a study will detect a real effect, if it exists. Higher power means a better chance of avoiding a false negative (missing a real effect). See power analysis below.

A planning step researchers do before a study starts to figure out how many participants need to be in the study. The goal is to have a large enough study to spot a real difference, if one exists, and not miss it because the study was too small. Researchers often aim for an ~80% chance of detecting a real effect and use a standard cutoff (often 0.05) to decide whether a result is likely due to chance.

A written draft of a scientific paper that describes research findings, usually submitted to a journal for possible publication.

The process in which other experts in the field check a scientific manuscript before it is published, to ensure the research is valid and meets quality standards.

A short summary of a research study, usually highlighting the study objective, methods, key findings, and conclusions.

A way of sharing research at a conference using a large printed poster with text, graphs, and images that summarize the study. Researchers stand by it to discuss findings and answer questions from conference attendees.

A professional meeting where researchers present their work (through talks, posters, or panels) and exchange ideas with others in the field.

Also known as a “Clinical Study.” A research study where people are given a treatment, procedure, or behavior change to test if it’s safe and works. Clinical trials can differ in design with some being more prone to bias and others, like RCTs (defined below), being more rigorous.

A type of clinical trial in which participants are randomly assigned to different groups (e.g., treatment vs. placebo). This reduces bias and is considered the “gold standard” for testing interventions.

A study where researchers just watch and measure health outcomes without giving a specific treatment.

Research that tests new treatments or ideas in animals, often before trying them in humans, to see if they might be safe or effective.

Experiments done outside of a living body, usually in test tubes or petri dishes (e.g., testing cells in a lab).

Studies that combine results from many randomized controlled trials on the same topic. A systematic review carefully collects and evaluates all high-quality studies. A meta-analysis uses statistics to pool the results, giving a stronger overall conclusion.

Research (often lab-based) that explores how something works biologically. For example, how a bioactive ingredient affects cells or chemical pathways.