Cited by 734Statistical Methods in Clinical TrialsMeta-analysis and systematic reviewsHealth Policy Implementation Science

Guidelines for designing and evaluating feasibility pilot studies

Open access
Teresi, Jeanne A., Yu, Xiaoying, Stewart, Anita L., Hays, Ron D.·2022·Medical Care

Abstract

BACKGROUND: Pilot studies test the feasibility of methods and procedures to be used in larger-scale studies. Although numerous articles describe guidelines for the conduct of pilot studies, few have included specific feasibility indicators or strategies for evaluating multiple aspects of feasibility. In addition, using pilot studies to estimate effect sizes to plan sample sizes for subsequent randomized controlled trials has been challenged; however, there has been little consensus on alternative strategies. METHODS: In Section 1, specific indicators (recruitment, retention, intervention fidelity, acceptability, adherence, and engagement) are presented for feasibility assessment of data collection methods and intervention implementation. Section 1 also highlights the importance of examining feasibility when adapting an intervention tested in mainstream populations to a new more diverse group. In Section 2, statistical and design issues are presented, including sample sizes for pilot studies, estimates of minimally important differences, design effects, confidence intervals (CI) and nonparametric statistics. An in-depth treatment of the limits of effect size estimation as well as process variables is presented. Tables showing CI around parameters are provided. With small samples, effect size, completion and adherence rate estimates will have large CI. CONCLUSION: This commentary offers examples of indicators for evaluating feasibility, and of the limits of effect size estimation in pilot studies. As demonstrated, most pilot studies should not be used to estimate effect sizes, provide power calculations for statistical tests or perform exploratory analyses of efficacy. It is hoped that these guidelines will be useful to those planning pilot/feasibility studies before a larger-scale study.

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  • The sample size of the present study falls within the range recommended for pilot studies.

    “However, the sample size of the present study falls within the range recommended for pilot studies (Lancaster et al., 2004; Teresi et al., 2022).”

    From Evaluation of effectiveness and acceptability of a psychological treatment for smoking cessation combined with a smartphone App: A pilot study (2024) · cites this paper as Teresi et al., 2022

    The ‘Sample Sizes for Pilot Feasibility Studies’ section gives conditional guidance: 30 per group may be adequate for quantitative feasibility studies, while some estimation goals may require 70–100 per group. It does not specify a single recommended range or establish that the citing study’s sample size fits the guidance; that depends on the study’s size and aims. (LLM, conf=0.82)

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  • The study aimed to recruit 80 participants to allow a 25% attrition rate and a final sample of 40 participants, appropriate for pilot feasibility studies.

    “The study aimed to recruit 80 participants to allow a 25% attrition rate and a final sample of 40 participants, appropriate for pilot feasibility studies (Creswell & Creswell, 2022; Teresi et al., 2022).”

    From Acceptance and Commitment Therapy Tele-Counselling Program With Care Partners of Persons Living With Dementia: A Pilot Feasibility RCT. (2026) · cites this paper as Teresi et al., 2022

    The ‘Sample Sizes for Pilot Feasibility Studies’ section says sample size depends on the feasibility goals and that 30 participants per group may be adequate for some quantitative studies. It does not establish that a final sample of 40 is appropriate for this particular study; the recruitment and attrition figures describe the citing authors’ own plan, not a finding attributed to Teresi et al. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 2

  1. [23]Jones RN, Tommet D, Ramirez M, Differential item functioning in Patient-reported Outcomes Measurement Information System (PROMIS®) physical functioning short forms. Psychol Test Assess Model 2016; 58(2): 371– 402.
  2. [42]Fleiss JL, Levin B, Paik MC. Stastical methods for rates and proportions. 3rd ed. Hoboken, N.J.: John Wiley & Sons, Inc.; 2003.

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Authors
Teresi, J. A., Yu, X., Stewart, A. L., & Hays, R. D.
Affiliations
  • Hebrew Home (US)
  • The University of Texas Medical Branch at Galveston (US)
  • University of California, San Francisco (US)
  • University of California, Los Angeles (US)
Corresponding author
Teresi, Jeanne A.
Venue
Medical Care
Published
2021-11-23
Volume
60
Issue
1
Pages
95-103
ISSN
0025-7079 (ISSN-L)
OpenAlex
W3215891836
Cited by
734
References
46
Citations by year
2026: 280 · 2025: 279 · 2024: 141 · 2023: 26 · 2022: 7
FWCI
32.16
Type
journal article
Language
en
Open access
Locations
  • Medical Care (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
  • National Institutes of Health (2p30ag028741-16)
  • University of California, San Francisco
  • National Institute on Aging (P30‐AG028741, P30AG059303, P30AG059301, P30AG021684, P30AG015272, P30AG022845)
  • National Institute of Allergy and Infectious Diseases
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (K12HD052023)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
Keywords
effect size estimation, sample size determination, randomized controlled trials, recruitment and retention, intervention fidelity, treatment acceptability, adherence, participant engagement, intervention adaptation, minimally important difference, confidence intervals, nonparametric statistics, design effect
MeSH terms
Feasibility Studies, Humans, Pilot Projects, Research Design, Guidelines as Topic

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