To examine preferences for HIV test methods using conjoint analysis, a method used to measure economic preferences (utilities).
Self‐administered surveys at four publicly funded HIV testing locations in San Francisco, California, between November 1999 and February 2000 (=365, 96 percent response rate).
We defined six important attributes of HIV tests and their levels (location, price, ease of collection, timeliness/accuracy, privacy/anonymity, and counseling). A fractional factorial design was used to develop scenarios that consisted of combinations of attribute levels. Respondents were asked 11 questions about whether they would choose “Test A or B” based on these scenarios.
We used random effects probit models to estimate utilities for testing attributes. Since price was included as an attribute, we were able to estimate willingness to pay, which provides a standardized measure for use in economic evaluations. We used extensive analyses to examine the reliability and validity of the results, including analyses of: (1) preference consistency, (2) willingness to trade among attributes, and (3) consistency with theoretical predictions.
Respondents most preferred tests that were accurate/timely and private/anonymous, whereas they had relatively lower preferences for in‐person counseling. Respondents were willing to pay an additional $35 for immediate, highly accurate results; however, they had a strong disutility for receiving immediate but less accurate results. By using conjoint analysis to analyze new combinations of attributes, we found that respondents would most prefer instant, highly accurate home tests, even though they are not currently available in the U.S. Respondents were willing to pay $39 for a highly accurate, instant home test.
The method of conjoint analysis enabled us to estimate utilities for specific attributes of HIV tests as well as the overall utility obtained from various HIV tests, including tests that are under consideration but not yet available. Conjoint analysis offers an approach that can be useful for measuring and understanding the value of other health care goods, services, and interventions.
