A simple formula for the calculation of sample size in pilot studies
Open accessAbstract
One of the goals of a pilot study is to identify unforeseen problems, such as ambiguous inclusion or exclusion criteria or misinterpretations of questionnaire items. Although sample size calculation methods for pilot studies have been proposed, none of them are directed at the goal of problem detection. In this article, we present a simple formula to calculate the sample size needed to be able to identify, with a chosen level of confidence, problems that may arise with a given probability. If a problem exists with 5% probability in a potential study participant, the problem will almost certainly be identified (with 95% confidence) in a pilot study including 59 participants.
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To detect a feasibility issue that has a 10% likelihood of occurrence, a sample size of 30 participants is required to identify the feasibility issue with a 95% CI.
“According to Viechtbauer et al [19], to detect a feasibility issue that has a 10% likelihood of occurrence, a sample size of 30 participants is required to identify the feasibility issue with a 95% CI.”
From Feasibility and Preliminary Efficacy of a “Sit Less” Program Leveraging Fitbit Tracking and Tailored Text Messages in Cardiometabolic Disease: Findings From 2 Parallel Randomized Controlled Trials in Coronary Artery Disease and Type 2 Diabetes (2026) · cites this paper as [19]
Section 3 states that screening 29 participants is sufficient to be 95% confident of encountering at least one problem that occurs with at least 10% probability. Thirty participants would also suffice, but the paper does not say 30 are required. The 95% figure is a probability of detecting the problem, not a confidence interval for its identification; the paper discusses confidence intervals separately in Additional information. (LLM, conf=0.88)
Experimental — accuracy not yet measuredAt least 29 participants are sufficient to detect problems with a probability of 0.10 and a 95% confidence interval.
“Viechtbauer et al. (2015) stated that at least 29 participants are sufficient to detect problems with a probability of 0.10 and a 95% confidence interval.”
From Feasibility of a Software agent providing a brief Intervention for Self-help to Uplift psychological wellbeing (“SISU”). A single-group pretest-posttest trial investigating the potential of SISU to act as therapeutic agent (2021) · cites this paper as Viechtbauer et al., 2015
Section 3, “Sample size calculations in practice,” states that screening 29 participants gives 95% confidence of encountering at least one case when the problem occurs with probability at least 0.10. The source calls this a 95% confidence level for detection, not a 95% confidence interval; Section “Additional information” discusses confidence intervals separately. (LLM, conf=0.86)
Experimental — accuracy not yet measured
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- Authors
- Viechtbauer, W., Smits, L., Kotz, D., Budé, L., Spigt, M., Serroyen, J., & Crutzen, R.
- Affiliations
- Maastricht University (NL)
- Corresponding author
- Crutzen, Rik
- Venue
- Journal of Clinical Epidemiology
- Publisher
- Elsevier BV
- Published
- 2015-11
- Volume
- 68
- Issue
- 11
- Pages
- 1375-1379
- ISSN
- 0895-4356 (ISSN-L)
- OpenAlex
- W1763526952
- Cited by
- 612
- References
- 15
- Citations by year
- 2026: 56 · 2025: 91 · 2024: 93 · 2023: 82 · 2022: 77 · 2021: 69 · 2020: 50 · 2019: 39 · 2018: 31 · 2017: 16 · 2016: 8
- FWCI
- 16.32
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Clinical Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, other-oa)
- Lirias (submittedVersion)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- sample size determination, pilot study, problem identification, inclusion and exclusion criteria, statistical power
- MeSH terms
- Humans, Pilot Projects, Sample Size, Mathematical Concepts
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