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Beyond the five-user assumption: benefits of increased sample sizes in usability testing.

It is widely assumed that 5 participants suffice for usability testing. In this study, 60 users were tested and random sets of 5 or more were sampled from the whole, to demonstrate the risks of using only 5 participants and the benefits of using more. Some of the randomly selected sets of 5 participants found 99% of the problems; other sets found only 55%. With 10 users, the lowest percentage of problems revealed by any one set was increased to 80%, and with 20 users, to 95%.

Consumer Behavior↗

Power and sample size.

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Data Interpretation, Statistical↗

Use of confidence intervals and sample size calculations in health economic studies.

OBJECTIVE: To discuss the calculation and application of confidence intervals in pharmacoeconomic studies. DATA SYNTHESIS: The increasing frequency with which pharmacoeconomic evaluations are made within clinical trials makes it possible to obtain information on the outputs and costs of an intervention in each patient of a sample under study. This allows the same statistical principles commonly used in clinical trials to be applied to cost or cost-effectiveness data. The methodology described in this article would allow expression of cost-effectiveness ratios in the form of confidence intervals. The calculation of the cost-effectiveness ratio by means of a confidence interval may have important practical consequences, both in decision-making on the choice of 1 intervention versus another and in calculating the size of the sample necessary to identify statistically significant differences, from both clinical and economic points of view. CONCLUSIONS: The complementary use of confidence intervals and sensitivity analysis makes it possible to measure uncertainty related and unrelated to variability in sample data, allowing the decision to adopt 1 technology or another to be based on the most objective information available. Although several ethical and methodologic concerns remain to be addressed, this methodology may contribute to improving the more rational and efficient use of drugs.

Confidence Intervals↗