Should You Test Recruitment Feasibility Before Finalizing the Study?

When should recruitment assumptions be tested rather than merely estimated?

Every study begins with assumptions about recruitment. Perhaps you expect a certain percentage of invited participants to respond. You assume that enough will satisfy the eligibility criteria, that cooperating sites can generate a particular number each month, or that a recruitment channel will reach the population you need.

Sometimes those assumptions are supported well enough by previous studies, institutional records, or recent experience that a separate recruitment test would add little. In other cases, the entire study depends on recruitment behavior for which you have weak or indirect evidence.

That is where testing recruitment feasibility becomes useful. Instead of asking only whether your recruitment plan sounds reasonable, you obtain empirical evidence about whether the pathway performs well enough to support the proposed study.

Test recruitment when unresolved uncertainty could determine whether the study succeeds

A recruitment feasibility test should answer a decision, not merely produce a pilot sample

First ask whether recruitment uncertainty is important enough to test

Testing recruitment takes time and resources, and it may require ethical, institutional, site, or other approvals depending on what the test involves. It should therefore address a genuine uncertainty.

A separate test may be unnecessary when recruitment has been demonstrated recently in essentially the same population, setting, study conditions, and recruitment pathway, particularly when the available pool is comfortably larger than the required sample.

Testing becomes more useful when the proposed population is difficult to reach, eligibility is uncertain, participation is burdensome, the recruitment channel is untested, several gatekeepers are involved, recruitment must occur quickly, or the sample requirement leaves little margin for disappointing enrollment.

The broader question is how much recruitment uncertainty your study can reasonably tolerate before it begins. A feasibility test is one way of reducing consequential uncertainty. It is not an obligatory ritual for every project.

Define what successful recruitment would have to look like

A feasibility test is difficult to interpret unless you know what recruitment performance the eventual study requires.

Suppose the main study needs 360 participants and has 12 months available for recruitment. Ignoring any planned variation over time, that corresponds to an average of 30 enrolled participants per month. A pilot that recruits eight people in one month has demonstrated that recruitment is possible. It has not demonstrated that recruitment is adequate for the proposed main study.

Recruitment-feasibility research emphasizes specifying recruitment goals and assessing whether those goals are met. The benchmark should therefore come from the demands of your study rather than from an arbitrary percentage borrowed from an unrelated project.

Test the whole recruitment pathway where possible

Final enrollment alone tells you whether recruitment underperformed. It does not necessarily tell you why.

A more informative feasibility assessment follows potential participants through the major stages of recruitment:

Tracking losses and reasons at each stage can identify whether the problem lies in reach, contact, eligibility, willingness, or another part of the recruitment system. Published recruitment-feasibility frameworks specifically recommend systematic tracking because weak links can then inform modifications to the larger study.

Measure recruitment speed, not just the total recruited

A recruitment test should usually record time. Ten enrollments obtained in one week and ten obtained over six months have very different implications for a study that needs 300 participants.

A simple planning calculation can make the connection explicit:

Recruitment may accelerate after sites become familiar with procedures or slow once the easiest participants have been approached. For that reason, a very short test may provide a misleading estimate of sustained recruitment performance.

Test conditions that resemble the study you actually plan to conduct

A feasibility test is most informative when the recruitment process resembles the future study.

If the principal investigator personally calls every potential participant during the pilot but the main study will rely on automated emails, the pilot has tested a different recruitment system. Similarly, unusually intensive staff support, temporary advertising funds, exceptional gatekeeper involvement, or a highly productive site can make pilot recruitment appear easier than what the main study can sustain.

Before extrapolating from the test, compare recruitment personnel, sites, communication channels, eligibility criteria, participant burden, incentives where applicable, screening procedures, and available resources with those planned for the full study.

Consider progression criteria before collecting feasibility data

For some pilot and feasibility studies, researchers specify progression criteria in advance. These criteria connect observed feasibility results to decisions about whether and how the larger study should proceed.

A traffic-light approach is sometimes used. A result in a green range may support proceeding, an amber range may indicate that modifications are required, and a red range may indicate that recruitment is unlikely to support the proposed study without substantial redesign.

The thresholds should be justified for the actual project. There is no universal recruitment percentage that makes every study feasible. A threshold is useful only when it corresponds meaningfully to the performance required by the proposed study.

Recruitment failure can be useful evidence

A feasibility test that reveals poor recruitment has not necessarily failed. It may have prevented a much larger failure.

Suppose the test reveals that only 10% of contacted people qualify when planning assumed 40%, or that a gatekeeper distributes invitations much less frequently than anticipated. Discovering this while the study can still be redesigned is precisely the kind of information feasibility work is intended to provide.

Empirical studies have shown how recruitment problems can remain consequential even after earlier feasibility work. In the HIMALAIA study, for example, recruitment in the main trial proved substantially slower than anticipated despite a preceding feasibility pilot, and the trial was eventually halted for insufficient recruitment. The case illustrates both the value and the limits of extrapolating recruitment performance from preliminary evidence.

A feasibility test does not have to answer the scientific research question

The primary purpose of a recruitment feasibility test is methodological: can the recruitment system work well enough for the intended study?

It should not be treated as a miniature hypothesis test whose success depends on obtaining a statistically significant substantive result. Pilot and feasibility studies are generally designed around uncertainties relevant to the future definitive study, with data collection and analysis aligned to those feasibility objectives.

Testing whether an ambitious recruitment plan can actually deliver

Recruitment testing is useful only when it resembles the problem you need to solve

Test recruitment when the decision value justifies the effort

A useful feasibility test sits between casual optimism and an unnecessary pilot. It should address uncertainty that could materially change your decision about the study.

The purpose is not to eliminate all uncertainty. Research rarely offers that luxury. The aim is to avoid building an expensive or time-sensitive study on a recruitment assumption that could have been tested while the design was still flexible.

Before testing recruitment feasibility, decide what the test must tell you

Questions about testing recruitment before the full study

Test recruitment when the study depends on an uncertain recruitment assumption

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