01 · The Question
Your population may be large, but how many people actually qualify?
Suppose your study needs 120 participants. You identify a university with 8,000 students, a hospital serving thousands of patients, or an online community with tens of thousands of members. At first glance, the numbers look reassuring.
But the size of the broader population is not the number that determines whether your study can recruit enough participants. What matters is how many people satisfy all of your inclusion and exclusion criteria.
A study might require participants to belong to a particular age group, have a specific experience or diagnosis, meet a minimum exposure threshold, live in a certain location, and have none of several exclusion conditions. Each criterion can narrow the pool. By the time the criteria are applied together, a seemingly abundant population may contain relatively few eligible people.
This creates a feasibility question that should be considered before you commit to the study: do enough eligible participants actually exist within the population you can realistically draw from?
02 · The Short Answer
Estimate the eligible pool, not merely the population size
In Brief
You can judge whether enough eligible participants exist by estimating how many people in the population available to your study are likely to satisfy all of your inclusion and exclusion criteria, then comparing that pool with the number your study needs.
A large population does not guarantee a large eligible pool. The most useful estimate comes from evidence such as administrative records, previous studies, screening data, preliminary counts from study sites, or a small feasibility assessment rather than an unsupported assumption about how common eligible participants are.
03 · What You Need to Know
Move from the visible population to the genuinely eligible population
Start with the population you could realistically draw from
The first number to establish is not necessarily the total number of people who theoretically belong to your target population. It is the number who could plausibly enter your recruitment pathway during the period and within the settings covered by your study.
Imagine that your target population is secondary-school teachers in a province. There may be 12,000 teachers in the province, but if your study has permission to recruit only from schools containing 2,400 teachers, the larger figure is not a useful starting denominator. Your feasibility estimate should begin with those 2,400 potentially available individuals.
This distinction matters because a population can exist in principle without being available through the settings and recruitment channels open to you . Eligibility and accessibility are related feasibility questions, but they are not the same question.
Potentially available does not mean eligible
Eligibility is determined by the criteria defined in your study protocol. Someone may belong to the general population of interest but fail to qualify because one or more criteria are not satisfied.
Researchers studying recruitment sometimes describe the eligibility fraction as the proportion of screened potential participants who are found to be eligible. This is useful because it separates two quantities that are easy to confuse: how many people enter the screening pool and how many survive the eligibility assessment.
Potentially available population
People who could plausibly enter your recruitment or screening process.
Eligible population
People within that pool who satisfy all relevant inclusion and exclusion criteria.
If 1,000 people are potentially available but only 20% satisfy the criteria, your estimated eligible pool is about 200, not 1,000.
Apply the criteria together, not one at a time in isolation
The difficulty often appears when several individually reasonable eligibility requirements intersect.
Suppose a study requires university students who are at least 18 years old, currently enrolled full time, have used a particular learning platform for at least one semester, belong to a particular academic program, and have completed a specific course. You cannot establish feasibility merely by finding that many students are adults, that many use the platform, and that many have completed the course. You need an estimate of how many satisfy the combination .
This is particularly consequential when criteria describe uncommon characteristics. A moderately restrictive criterion may appear harmless on its own, yet several such criteria can reduce the eligible pool sharply. Studies involving rare or hard-to-reach populations require especially careful estimation because the initial pool may already be small.
Use the strongest evidence you can reasonably obtain
The precision of your estimate will depend on what information exists before the study begins. You rarely need to know the exact number of eligible participants in advance, but you should avoid pretending that a guess is an estimate.
Useful evidence may come from institutional or administrative records, anonymized aggregate counts from a prospective study site, prior research involving a sufficiently comparable population, service or program records, registry information, or preliminary screening data. When appropriate, you may also ask a potential site or data custodian whether aggregate information is available before finalizing the protocol.
If access depends on an institution, it can therefore be useful to contact potential sites or data providers before finalizing the research question . The purpose is not to begin recruiting participants prematurely. It is to determine whether the assumptions underlying the proposed study are plausible and what information can legitimately be provided before formal approval.
Watch Out
Do not obtain identifiable participant information or begin screening people merely to answer a preliminary feasibility question unless the necessary ethical and institutional permissions are already in place. Aggregate counts, appropriately authorized feasibility queries, and other non-identifiable information may often be sufficient at the planning stage, subject to local requirements.
Calculate a plausible range when the eligibility rate is uncertain
Sometimes you know the size of the potentially available pool but not the exact proportion that will qualify. In that situation, a range is usually more defensible than a single optimistic estimate.
For example, suppose 600 people could plausibly be screened and available evidence suggests that perhaps 30% to 50% will satisfy the eligibility criteria. Your plausible eligible pool would be approximately 180 to 300 people.
This simple sensitivity check changes the question from “Do we have 600 possible participants?” to “Would the study remain plausible if eligibility is toward the lower end of what we expect?” That is a much more useful feasibility question.
Do not stop at the sample-size requirement
If your analysis requires 150 participants and you estimate that exactly 150 eligible people exist, the study is not comfortably feasible. That scenario effectively assumes that every eligible person can be identified, approached, and enrolled.
Eligibility is only one stage of recruitment. Eligible people may never be reached, may decline participation, may not complete enrollment procedures, or may become unavailable. Research on recruitment therefore distinguishes the eligibility fraction from the enrollment fraction, which concerns the proportion of eligible people who actually enroll. These quantities can differ substantially across studies and settings. Published research has also documented considerable variation in how many people must be screened to obtain enrolled participants.
For this reason, establishing that enough eligible people exist answers only one part of whether you can actually recruit the participants your study requires . Whether those people will agree to participate is a separate question.
Your eligibility criteria themselves may be creating the shortage
If the estimated pool is too small, inspect the criteria before concluding that the entire research question is impossible.
Ask why each criterion exists. Some criteria are scientifically necessary because removing them would change the population to which the research question applies. Others may be required for safety, ethics, measurement validity, or study design. But occasionally a criterion survives simply because it appeared in an earlier proposal or seemed convenient when the study was conceived.
Removing a defensible criterion merely to make recruitment easier can damage the study. Keeping an unnecessary criterion can make an otherwise worthwhile study infeasible. The relevant question is therefore not simply whether a criterion reduces the pool, but whether the scientific or methodological reason for that restriction justifies the reduction.
04 · A Practical Example
How a population of 2,000 can become fewer than 100 eligible participants
Hypothetical Example
A study of students with sustained experience using an AI learning tool
A researcher plans a survey requiring 120 participants. A cooperating university has 2,000 students in the relevant colleges, so the researcher initially assumes that recruitment should be easy.
Start with the potentially available pool The participating colleges contain 2,000 students who could potentially be considered.
Apply the first major criterion Institutional aggregate data indicate that about 700 students are enrolled in the specific programs included in the study.
Apply the experience requirement Available course information suggests that approximately 240 of those students have taken courses in which the relevant AI tool was used.
Apply the duration requirement Only about 90 appear likely to satisfy the requirement for sustained use across at least two semesters.
Compare the eligible pool with the requirement The study needs 120 completed participants, but the preliminary estimate suggests that fewer than 100 people may even be eligible.
The problem was invisible when the researcher looked only at the university's 2,000 students. The study does not yet have a recruitment-rate problem. It has a more fundamental eligibility problem: the estimated pool of qualifying people may be smaller than the desired sample.
The researcher now has evidence to reconsider the design before investing heavily in recruitment. Possible responses include adding appropriate sites, reconsidering whether the two-semester requirement is scientifically necessary, revising the population or research question if justified, or conducting a more formal feasibility assessment before proceeding.
06 · What This Means for You
Decide whether your eligible pool gives the study enough room to work
You do not necessarily need a census of every eligible person before beginning a study. What you need is enough evidence to decide whether the proposed sample is plausible under realistic assumptions.
A simple decision framework
If the estimated eligible pool is comfortably larger than the required sample
Move on to assessing access, willingness to participate, recruitment rate, and the time available for enrollment.
If the estimated eligible pool is only slightly larger than the required sample
Treat feasibility as uncertain. Examine realistic enrollment assumptions and consider obtaining better eligibility information before committing.
If the estimated eligible pool is smaller than the required sample
Do not assume recruitment effort will solve the problem. Reconsider sites, scientifically defensible eligibility criteria, sample requirements, design, or the research question itself.
If you cannot estimate the eligible pool with reasonable confidence
Make the uncertainty explicit and obtain stronger feasibility evidence rather than silently assuming that enough participants exist.
The appropriate margin between the estimated eligible pool and the required sample cannot be reduced to one universal ratio. It depends on how many eligible people can actually be identified and approached, anticipated willingness to participate, recruitment duration, number of sites, study burden, and other features of the recruitment pathway.
Where the uncertainty is consequential, the next step may be to estimate eligibility more systematically before committing to the study or to test recruitment feasibility before finalizing the design .
07 · A Quick Checklist
Before assuming enough eligible participants exist, check these
Before committing to the participant pool, check:
Define the inclusion and exclusion criteria precisely enough to determine who actually qualifies.
Identify the population that could realistically enter your recruitment pathway, not merely the total theoretical population.
Estimate how many people satisfy all important criteria together.
Use administrative counts, site information, previous research, screening records, or other defensible evidence where available.
Use a plausible range rather than a single optimistic estimate when the eligibility rate is uncertain.
Compare the estimated eligible pool with the number of enrolled or completed participants your study ultimately requires.
Remember that some eligible people will not necessarily enroll, so eligibility alone does not establish recruitment feasibility.
Review whether every restrictive eligibility criterion has a defensible scientific, methodological, ethical, or safety rationale.
Investigate major uncertainty before finalizing a design that depends on optimistic eligibility assumptions.
11 · Cite this Guide
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