Examining the effects of prevention programs on the incidence of new cases of mental disorders: the lack of statistical power

In the past few decades about 1,000 controlled studies have examined the effects of mental health prevention programs, but few studies have examined the effects of such programs on the incidence of new cases of mental disorders defined according to diagnostic criteria. A major reason why so few stud...

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Vydáno v:The American journal of psychiatry Ročník 160; číslo 8; s. 1385
Hlavní autor: Cuijpers, Pim
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States 01.08.2003
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ISSN:0002-953X
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Shrnutí:In the past few decades about 1,000 controlled studies have examined the effects of mental health prevention programs, but few studies have examined the effects of such programs on the incidence of new cases of mental disorders defined according to diagnostic criteria. A major reason why so few studies have examined this important question is that very large numbers of subjects are needed to provide sufficient statistical power for these studies. In this article this power problem is explored. Power calculations are presented for studies examining universal prevention (aimed at the general population regardless of risk status), selective prevention (aimed at high-risk groups), and indicated prevention (aimed at subjects who have some symptoms of a disorder without meeting full diagnostic criteria). Studies examining universal prevention are hardly feasible, as the number of subjects required amounts to tens of thousands at least. Research examining selective prevention is more feasible, but the number of subjects needed for these studies is still very high. Studies of indicated prevention are possible. Three major studies of indicated prevention examining the effects on the incidence of new cases of mental disorders are described. There are several strategies for increasing statistical power in prevention studies: 1) focus on high-incidence groups (by concentrating on indicated prevention, by targeting high-risk groups with multiple risk factors, by targeting groups with multiple disorders), 2) strengthen the effects of prevention programs, and 3) make more efficient use of other trials through cumulative meta-analyses.
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ISSN:0002-953X
DOI:10.1176/appi.ajp.160.8.1385