Risk indicators only indicate that there is an association between the variable and the onset, while no causal association is assumed. In principle, these risk indicators can be used to identify target groups for preventive interventions. In the next part of this paper, we will show that several groups of interventions actually have focused
on such high-risk groups. Although many risk indicators are known to be associated with the onset of mental disorders, most of them have a low specificity. This low specificity implies that most subjects who are exposed to the risk factor do not develop the disorder, and that one such risk factor by itself is not sufficient to bring the disorder into Inhibitors,research,lifescience,medical being.50,51 Furthermore, most risk indicators are related to lifetime risk, while target populations for preventive interventions must have an increased risk at the shorter term. Suppose, for example, that the risk of developing a major depressive disorder in the general Wnt inhibitor population is
2.5% in 1 year.52,53 If a high-risk group has a relative Inhibitors,research,lifescience,medical risk of developing a depressive disorder of 4.00, this will be highly significant (if the research Inhibitors,research,lifescience,medical population is large enough). However, this means that still only about 10% of the high-risk group will actually develop a depressive disorder, and about 90% will not. Many epidemiological researchers are satisfied after finding a highly significant relative risk of 4.00, but from the point of view of prevention this is clearly not enough. A high-risk group will probably be difficult Inhibitors,research,lifescience,medical to motivate for participation in a preventive program if only 10% eventually will develop the disorder, apart from the question of whether it is ethically acceptable to identify such a population as being “at risk” when most are in fact not at risk, or to intervene in such a population when for the vast Inhibitors,research,lifescience,medical majority of participants the intervention is not needed, and thus the time they spend on it is, in a sense, wasted. Furthermore, such an intervention is probably not very efficient or cost-effective, because the majority will never develop a disorder and the intervention has no preventive effect in this majority. From the perspective of preventive
intervention research, this low specificity is also problematic because very large numbers of subjects are needed to provide all sufficient statistical power for these intervention studies.51 Suppose, for example, that we would be able to motivate people from the high-risk group (10% of whom will develop a mental disorder in the following year) to participate in a preventive intervention. In order to show that such an intervention is capable of reducing the incidence from 10% to 5% (a risk reduction of 50%), we would need about 950 persons in a controlled trial (assuming a statistical power of 0.80; alpha level 0.05; calculations in STATA/SE 8.2). Trials of this size are logistically complex, expensive, and have a high risk of failure.
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