TY - JOUR
T1 - Guidelines for Designing and Evaluating Feasibility Pilot Studies
AU - Teresi, Jeanne A.
AU - Yu, Xiaoying
AU - Stewart, Anita L.
AU - Hays, Ron D.
N1 - Funding Information:
This article was a collaboration of the Analytic Cores from several National Institute on Aging Centers: Resource Centers for Minority Aging Research (UCSF, grant number 2P30AG015272-21, Karliner; UCLA, grant number P30-AG021684, Mangione; and University of Texas, grant number P30AG059301, Markides), an Alzheimer’s Disease—RCMAR Center (Columbia University, grant number 1P30AG059303, Manly, Luchsinger) an Edward R. Roybal Translational Research Center (Cornell University, grant number 5P30AG022845, Reid, Pillemer, and Wethington), and the Measurement Methods and Analysis Core of a Claude D. Pepper Older Americans Independence Center (National Institute on Aging, 1P30AG028741, Siu). These funding agencies played no role in the writing of this manuscript. X.Y. is supported by a research career development award (K12HD052023: Building Interdisciplinary Research Careers in Women’s Health Program-BIRCWH; Berenson, PI) from the National Institutes of Health/Office of the Director (OD)/National Institute of Allergy and Infectious Diseases (NIAID), and Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD).
Publisher Copyright:
© 2022 Lippincott Williams and Wilkins. All rights reserved.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - 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.
AB - 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.
KW - confidence intervals
KW - diversity
KW - feasibility
KW - guidelines
KW - pilot studies
KW - statistical issues
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U2 - 10.1097/MLR.0000000000001664
DO - 10.1097/MLR.0000000000001664
M3 - Article
C2 - 34812790
AN - SCOPUS:85120716358
SN - 0025-7079
VL - 60
SP - 95
EP - 103
JO - Medical Care
JF - Medical Care
IS - 1
ER -