Revised Centers for Disease Control and Prevention recommendations on HIV testing now
promote testing of most risk groups. However, positive results for low-risk individuals are more likely
to be false positives than for high-risk individuals, making clear communication of test results even
more imperative. In a study, we evaluated current counseling of low-risk test recipients via a sample of
29 HIV hotline counselors from U.S. state and national hotlines. 100% of counselors interviewed
failed to provide an accurate conditional HIV risk for low-risk women, but were more likely than a
1998 German sample to report that false positives could occur. In a second study, undergraduates read
idealized transcripts of interviews with HIV counselors and computed conditional risk for a low-risk
individual. The natural frequency format offered a small but significant improvement in conditional reasoning,
comparable to the effect of numerical literacy. Applications for ecologically valid numerical presentations of risk and
implications for numeracy are discussed.
Keywords: Bayesian reasoning, conditional risk, HIV counseling, HIV testing, numeracy, risk communication.
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