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Sample size for pre-tests of questionnaires.

Thomas V Perneger1, Delphine S Courvoisier, Patricia M Hudelson

  • 1Division of Clinical Epidemiology, University Hospitals of Geneva, 6 rue Gabrielle-Perret-Gentil, 1211, Geneva, Switzerland, thomas.perneger@hcuge.ch.

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Summary
This summary is machine-generated.

Pre-testing questionnaires with small samples (5-15 participants) may miss common issues. A recommended sample size of 30 enhances the detection of problems in psychometric instruments.

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Area of Science:

  • Psychometrics
  • Survey methodology
  • Health sciences research

Background:

  • Pre-testing is crucial for identifying issues in questionnaires.
  • Current pre-testing practices often use small sample sizes, potentially limiting effectiveness.

Purpose of the Study:

  • To determine the optimal sample size for pre-testing psychometric questionnaires.
  • To guide researchers in effectively detecting participant-encountered problems with instrument items.

Main Methods:

  • Calculated statistical power to detect problems across varying prevalence and sample sizes.
  • Determined the sample size needed to detect problems at different prevalence levels.
  • Computed upper confidence limits for problem prevalence when no issues were detected.

Main Results:

  • Power to detect problems increases with prevalence and sample size.
  • A sample of 32 is needed for 80% power to detect a 5% prevalence problem.
  • With no problems detected, a sample of 30 yields an upper confidence limit of 0.10 for problem prevalence.

Conclusions:

  • Small pre-test sample sizes (5-15) are insufficient for uncovering common questionnaire problems.
  • A default sample size of 30 participants is recommended for effective pre-testing.
  • Larger sample sizes improve the reliability of identifying and addressing instrument item difficulties.