Inclusion and Exclusion Criteria | Examples & Definition

Inclusion and exclusion criteria determine which members of the target population can or can’t participate in a research study. Collectively, they’re known as eligibility criteria, and establishing them is critical when seeking study participants for clinical trials.

This allows researchers to study the needs of a relatively homogeneous group (e.g., people with liver disease) with precision. Examples of common inclusion and exclusion criteria are:

  • Demographic characteristics: Age, gender identity, ethnicity
  • Study-specific variables: Type and stage of disease, previous treatment history, presence of chronic conditions, ability to attend follow-up study appointments, technological requirements (e.g., internet access)
  • Control variables: Fitness level, tobacco use, medications used

Failure to properly define inclusion and exclusion criteria can undermine your confidence that causal relationships exist between treatment and control groups, affecting the internal validity of your study and the generalisability (external validity) of your findings.

What are inclusion criteria?

Inclusion criteria comprise the characteristics or attributes that prospective research participants must have in order to be included in the study. Common inclusion criteria can be demographic, clinical, or geographic in nature.

Example: Inclusion criteria
You are running a clinical trial for a new treatment for individuals with chronic heart failure. The following inclusion criteria apply:

  • 18 to 80 years of age
  • Diagnosis of chronic heart failure at least 6 months before trial
  • On stable doses of heart failure therapies
  • Willing to return for required follow-up (posttest) visits

People who meet the inclusion criteria are then eligible to participate in the study.

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What are exclusion criteria?

Exclusion criteria comprise characteristics used to identify potential research participants who should not be included in a study. These can also include those that lead to participants withdrawing from a research study after being initially included.

In other words, individuals who meet the inclusion criteria may also possess additional characteristics that can interfere with the outcome of the study. For this reason, they must be excluded.

Typical exclusion criteria can be:

  • Ethical considerations, such as being a minor or being unable to give informed consent
  • Practical considerations, such as not being able to read

If potential participants possess any additional characteristics that can affect the results, such as another medical condition or a pregnancy, these are also often grounds for exclusion.

Example: Exclusion criteria
In the clinical trial for individuals with chronic heart failure, the following exclusion criteria apply:

  • The patient requires valve or other cardiac surgery
  • The patient is unable to carry out any physical activity without discomfort
  • The patient had a stroke within three months prior to enrollment
  • The patient refuses to give informed consent
  • The patient is a candidate for coronary bypass surgery or something similar

People who meet one or more of the exclusion criteria must be disqualified. This means that they can’t participate in the study even if they meet the inclusion criteria.

Examples of inclusion and exclusion criteria

It is important that researchers clearly define the appropriate inclusion and exclusion criteria prior to recruiting participants for their experiment or trial.

Example: Inclusion and exclusion criteria
Let’s say you are studying the effect of a relaxation therapy on women with insomnia.

Here are some examples of effective and ineffective ways to phrase your criteria:

Inclusion criteria

Bad example: ‘Subjects will be included in the study if they have insomnia’.

This is too vague. How are you going to establish that participants have insomnia?

Good example: ‘Subjects will be included in the study if they have been diagnosed with insomnia by a physician and have had symptoms (i.e., trouble falling and/or staying asleep) for at least 3 nights a week for a minimum of 3 months’.

Here, the diagnosis and symptoms are clear. Specifying the time frame ensures that the condition (insomnia) is more likely to be stable throughout the study.

Exclusion criteria

Bad example: ‘Subjects will be excluded from the study if they are taking medications’.

This is too broad. There are many forms of medication, and some surely will not interfere with your study results. Excluding anyone who is using any type of medication—be it painkillers, birth control, or antidepressants—makes recruitment of study participants for your sample difficult. This, in turn, affects the feasibility of your study.

Good example: ‘Subjects will be excluded from the study if they are currently on any medication affecting sleep, prescription drugs, or other drugs that in the opinion of the research team may interfere with the results of the study’.

This statement is more specific, allowing you to limit extraneous variables that you are reasonably sure will influence your data.

Researchers review inclusion and exclusion criteria with each potential participant to determine their eligibility.

Why are inclusion and exclusion criteria important?

Defining inclusion and exclusion criteria is important in any type of research that examines characteristics of a specific subset of a population. This helps researchers identify the study population in a consistent, reliable, and objective manner. As a result, study participants are more likely to have the attributes that will make it possible to robustly answer the research question.

In clinical trials, establishing inclusion and exclusion criteria minimises the likelihood of harming participants (e.g., excluding pregnant women) and safeguards vulnerable individuals from exploitation (e.g., excluding individuals who are unable to comprehend what the research entails.) Ethical considerations like these are critical in human-based research.

Keep in mind that researchers must be able to justify all inclusion and exclusion criteria added to their study. Unless the purpose of the research justifies the exclusion of a specific group, the research population should be as diverse as possible. The same goes for the risks and benefits associated with the study.

For example, in a study of prostate cancer, there would be no justification for excluding non-white men. But excluding women is justifiable due to the target population in this case being ‘people with prostates’.

The main goal of clinical trials is to prove that a medication is safe and effective when used by the target population it was designed for. Therefore, ensuring that study participants are representative of the target population is crucial to the success of the study.

By applying inclusion and exclusion criteria to recruit participants, researchers can ensure that participants are indeed representative of the target population, ensuring external validity. Relatedly, defining robust inclusion and exclusion criteria strengthens your claim that causal relationships exist between your treatment and control groups, ensuring internal validity.

Strong inclusion and exclusion criteria also help other researchers, because they can follow what you did and how you selected participants, allowing them to accurately replicate or reproduce your study.

Ethnographies and a few other types of qualitative research do not usually specify exclusion criteria. However, inclusion criteria help researchers define the community of interest—for example, users of Apple watches. In this way, they can find individuals who have attributes that can help them meet the goals of the study.

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Frequently asked questions about inclusion and exclusion criteria

What is the difference between internal and external validity?

Internal validity is the degree of confidence that the causal relationship you are testing is not influenced by other factors or variables.

External validity is the extent to which your results can be generalised to other contexts.

The validity of your experiment depends on your experimental design.

What type of sampling uses inclusion and exclusion criteria?

Inclusion and exclusion criteria are predominantly used in non-probability sampling. In purposive sampling and snowball sampling, restrictions apply as to who can be included in the sample.

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Kassiani Nikolopoulou

Kassiani has an academic background in Communication, Bioeconomy and Circular Economy. As a former journalist she enjoys turning complex scientific information into easily accessible articles to help students. She specialises in writing about research methods and research bias.