Risk Assessment: The Consumer as an Intuitive Statistician - Innovation and Marketing in the Pharmaceutical Industry - page 288

Thus, optimists' self-positivity bias remained significant, but was weaker for less
controllable events, consistent with Perloff and Fetzer's ( 1986 ) results. Lin et al.
( 2003 ) suggest that this was because optimists use self-positivity (the effect that
estimates of own risk are lower than estimates of the risk of other people), as a stra-
tegic device to maintain or enhance their self-esteem. Lin et al. ( 2003 ) also found
that pessimists (with high absolute levels of risk) demonstrated self-negativity (high
relative levels of risk) which is consistent with Keller et al.'s ( 2002 ) findings with
respect to breast cancer. The primary difference between optimists and pessimists
was in the extent to which they used contextually provided base rate information to
update their estimates of risk. While optimists had shown no or inadequate levels of
adjustment, pessimists readily updated their risk estimates using base rate informa-
tion, leading to an attenuation or elimination of their self-negativity bias. Said dif-
ferently, the diagnosticity of memory-based information (based on prior experience)
was lower for optimists as compared to pessimists.
Lin et al.'s ( 2003 ) framework allows for a reconciliation of the effects of depres-
sive realism with self-positivity. As depressives view their life and future in negative
terms (Beck 1967 , 1976 ), they have low levels of self-esteem (Gerrard et al. 2000 ),
resulting in their being pessimistic at an absolute level and not prone to self-
positivity at the relative level. The literature on self-positivity and self-negativity
shows the importance that base rates play in people's assessment of risk as well as
highlight the fact that risk estimates can be biased in either direction.
Given that both types of biases can lead to downstream consequences, the chap-
ter will examine ways in which risk estimates can be increased or decreased as war-
ranted, although as most work has found underestimation of risk, it will specifically
address interventions aimed at increasing risk estimates based on both the top-down
and the bottom-up processes.
We start with an overview of the two processes (bottom-up and top-down) of risk
estimation as laid out in Fig. 10.1 . For each process, we describe the basic inputs
that are used, and the sources of bias that creep in as there is a departure of perceived
risk from actual risk. It is within this context that prior literature that has examined
specific factors affecting risk estimates is reviewed; we then go on to ask: how do
consumers combine top-down base rate information about the likelihood of occur-
rence of a disease with bottom-up information about their own or others' risk fac-
tors to assess how much at risk they or others are, and whether they should seek
treatment? The chapter concludes with some important and open research questions
for risk perceptions.

10.4 The Effect of Risk Factors on Risk Assessment:

The Bottom-up Process

The bottom-up process, frequently used in demand estimation, is characterized by
working up the individual (or segment) likelihood of various consumers performing a
series of probabilistic actions that then aggregate to a macro-assessment of market size.