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# Study population and selection criteria

- Concept

Who the result is meant for, who can be reached and who actually enters the study, according to written criteria.

Updated Nov 13, 2026

## Key points

- Target → accessible → sample: representativeness can be lost at each step.
- Exclusion criteria are not the opposite of inclusion criteria: they remove eligible people for safety, inability to follow up or unreliable data.
- Very strict criteria raise internal validity and homogeneity but reduce applicability.
- The full flow is reported: screened, eligible, enrolled, followed and analysed (flow diagram).
- Those who agree are compared with those who refuse or are lost, to judge selection bias.

On this page

- The basics Key points
- What it is
- Key facts
- Worked example
- The three levels of population
- Markers
- In practice
- Common pitfalls
- Memory aid

- Study Test yourself

- Connections Connections

## What it is

The target population is the one the result is meant to apply to; the accessible population is the part of it the team can reach (a hospital, a town); and the study population, or sample, is those who finally take part. Inclusion criteria define who has the condition of interest, and exclusion criteria remove people who, although eligible, would be at risk or would give unreliable data. How participants are chosen, recruited and retained decides the representativeness and validity of the study.

## Key facts

- Participation rate = enrolled / eligible. Retention = completed follow-up / enrolled.
- Recruitment strategies: consecutive enrolment, several sites, community partners; retention: back-up contacts, reminders, short and flexible visits.

## Worked example

- Target population: adults with hypertension in a town, about 18 000. Accessible: those registered at 3 providers (IPS), 4 200.
- 600 consecutive people are screened. 90 do not meet the inclusion criteria and 60 have an exclusion criterion.
- Eligible: 600 − 90 − 60 = 450. 360 agree and sign consent: 360 / 450 = 80 %.
- At 12 months, 324 complete follow-up: retention 324 / 360 = 90 %.
- Of those screened, 324 / 600 = 54 % finish; everything is summarised in a flow diagram.
- Those who refused were younger (mean age 44 vs 58 years): the sample under-represents young adults.
- Reading: the result applies well to the older accessible population; to generalise it to the 18 000, that difference must be weighed.

## The three levels of population

| Level | What it is | Example |
| --- | --- | --- |
| Target population | Whom the result is meant to apply to | Adults with hypertension in the town |
| Accessible population | The part of the target that can be reached | People registered at 3 IPS |
| Study population (sample) | Those who meet the criteria, agree and take part | 360 enrolled |

## Markers

- Target
- Accessible
- Sample

## In practice

- When reading a trial, the baseline table and the selection criteria tell which patients the sample resembles.
- Excluding older people, pregnant women or people with several diseases leaves no data on groups seen every day.

## Common pitfalls

- Writing an exclusion criterion that is merely the opposite of an inclusion criterion.
- Not recording how many refused and why.
- Recruiting only highly motivated volunteers and generalising to the whole population.

## Memory aid

‘A three-stage funnel’: target, accessible and sample; at each stage, look at who was left outside.

## Test yourself

Think of the answer, then tap the question to see it.

## What is the difference between the target and the accessible population?

The target is whom the result is meant for; the accessible population is the part of it the team can reach.

## What are exclusion criteria for?

To remove eligible people for whom taking part would be risky or whose data would be unreliable or could not be followed up.

## Of 500 eligible people, 400 agree and 340 finish. What is the retention?

340 / 400 = 85 %.

## What happens to applicability when the selection criteria are very strict?

It falls: the sample resembles everyday patients less.

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## Connections

## Related 5

- [Selection bias](https://durgical.com/en/epidemiology/selection-bias/)
- [Sampling methods](https://durgical.com/en/epidemiology/sampling-methods/)
- [Internal and external validity](https://durgical.com/en/epidemiology/internal-and-external-validity/)
- [Attrition bias](https://durgical.com/en/epidemiology/attrition-bias/)
- [Randomised controlled trial](https://durgical.com/en/epidemiology/randomised-controlled-trial/)

[← All of epidemiology](https://durgical.com/en/epidemiology/)

Educational content on epidemiological and statistical methods; the examples use made-up numbers to teach the calculation. Not a clinical or legal guide: current Colombian rules are in the official sources.

Sources: [CONSORT 2025 Statement: updated guideline for reporting randomised trials](https://www.equator-network.org/reporting-guidelines/consort/) (EQUATOR Network, 2025); [Selection bias | Catalog of Bias](https://catalogofbias.org/biases/selection-bias/) (Catalogue of Bias Collaboration, 2017); [Collecting Data](https://www.cdc.gov/field-epi-manual/php/chapters/collecting-data.html) (Centers for Disease Control and Prevention (The CDC Field Epidemiology Manual), 2024).

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Representative model, for educational purposes only.

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License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Cite as: DurgiPedia (durgical.com), https://durgical.com/en/epidemiology/study-population-and-selection-criteria/
