Sex and Mortality: Real Risk and Perceived Vulnerability
Cohen, Dale J., Bruce, Katherine E., The Journal of Sex Research
The public's perceived susceptibility to health risks does not always accurately reflect the statistical estimates of actual risk (for review, see Weinstein, 1989). It is assumed that a discrepancy between perceived susceptibility and the epidemiological estimates of actual risk also exists for HIV infection. However, conclusive validation of this assumption is lacking. Rather than estimate participants' actual risk of HIV infection based on epidemiological data, researchers have tended to categorize various populations as "high" or "low" risk for HIV infection based on their assessment of the participants' reported behaviors (e.g., Bauman & Siegel, 1987; Gladis, Michela, Walter, & Vaughan, 1992; Hansen, Hahn, & Wolkenstein, 1990; van der Velde, van der Plight, & Hooykaas, 1994; for a discussion, see van der Pligt, Otten, Richard, & van der Velde, 1993). This methodological approach can lead to confusion concerning how "high risk" should be operationalized (e.g., what is the statistical probability of being infected if one is classified as "high risk?") and which reported behaviors define a "high risk" classification. Without consistent operational definitions of the various risk classifications, it is impossible to compare findings to the epidemiological estimates of actual risk for HIV infection (or even across studies).
Inconsistent operational definitions of various risk classifications have also led to different conclusions concerning whether behavioral changes should be expected for non-intravenous drug-using (non-IDU) heterosexual adults. For example, non-IDU heterosexual adults' reported high levels of risky sexual behavior have been interpreted as rational behavior based on the small likelihood that they would actually encounter a sexual partner with HIV infection (Fumento, 1990; Symons, 1993), rational behavior based on the assessment of the costs and benefits associated with sexual activity (Pinkerton & Abramson, 1992), and irrational behavior explained by their perceived unique invulnerability to HIV infection (Gerrard, Gibbons, & Warner, 1991; Gladis et al., 1992; Hansen et al., 1990; Mickler, 1993). At the heart of this debate is the disagreement concerning the probability that non-IDU heterosexual adults would contract HIV infection through unprotected sexual intercourse. The researchers using an explicit or implicit risk-classification technique do not quantify this probability. Without quantification, the debate cannot be resolved.
Another approach researchers have used to draw conclusions concerning the epidemiological accuracy of their participants' perceived probability of being infected with HIV has been to ask participants to estimate their likelihood of HIV infection (e.g., using percent probability of infection) and then make comparisons between the participants' estimates of their risk and the participants' estimates of the risk of another person who engages in similar behavior (e.g., Hansen et al., 1990; Mickler, 1993). Because the participants consistently estimate their risk as less than another's risk ("optimistic bias," Weinstein, 1989), the researchers concluded that participants do not have a realistic notion of their actual risk of HIV infection (e.g., Gladis et al., 1992; Hansen et al., 1990; Mickler, 1993). Although this method allows one to draw conclusions concerning personal vulnerability bias, it does not allow one to make conclusions concerning one's absolute risk. To draw conclusions concerning participants' realistic notions of a risk, the appropriate comparison is between the participants' estimates of their risk and the epidemiological estimates of their actual risk. Because the researchers never calculated the epidemiological estimates of the actual risks of their participants, their conclusions concerning their participants' realistic notions of HIV infection could not be validated. Resolving this issue is important because individuals' perceived susceptibility to HIV infection and its impact on their behavior is a key component in models that have been useful in designing and evaluating HIV-prevention programs (e. …