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Cited by 217Mental Health Treatment and AccessMeta-analysis and systematic reviewsStatistical Methods in Epidemiology

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

Cuijpers, Pim·2003·American Journal of Psychiatry
DOI 10.1176/appi.ajp.160.8.1385
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Abstract

Objective 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. Method 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). Results 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. Conclusions 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 f…

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  • The evidence for universal interventions is generally weak.

    “The evidence for universal interventions is generally weak, but conducting studies with a large enough sample size and consequently sufficient power to detect the very small effect sizes that are achievable if the interventions do work is challenging. 101”

    From The Lancet Psychiatry Commission on youth mental health (2024) · cites this paper as [101]

  • Conducting studies with a large enough sample size and sufficient power to detect the very small effect sizes achievable if universal interventions do work is challenging.

    “The evidence for universal interventions is generally weak, but conducting studies with a large enough sample size and consequently sufficient power to detect the very small effect sizes that are achievable if the interventions do work is challenging. 101”

    From The Lancet Psychiatry Commission on youth mental health (2024) · cites this paper as [101]

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Authors
Cuijpers, P.
Affiliations
Trimbos Institute (NL)
Corresponding author
Cuijpers, Pim
ORCID
Cuijpers, Pim
Venue
American Journal of Psychiatry
Publisher
American Psychiatric Association Publishing
Published
2003-08-01
Volume
160
Issue
8
Pages
1385-1391
ISSN
  • 0002-953X (ISSN-L)
  • 1535-7228
DOI
10.1176/appi.ajp.160.8.1385
OpenAlex
W2134404467
Cited by
217
References
9
Citations by year
2026: 5 · 2025: 4 · 2024: 5 · 2023: 25 · 2022: 10 · 2021: 10 · 2020: 10 · 2019: 11 · 2018: 8 · 2017: 14 · 2016: 6 · 2015: 8 · 2014: 9 · 2013: 11 · 2012: 11
FWCI
10.19
Type
journal article
Language
en
Open access
closed
Locations
  • American Journal of Psychiatry (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Psychology › Social Psychology › Mental Health Treatment and Access
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Keywords
mental health prevention programs, statistical power, sample size determination, universal prevention, selective prevention, indicated prevention, high-risk groups, cumulative meta-analysis
MeSH terms
Adolescent, Mental Disorders, Child, Data Interpretation, Statistical, Female, Humans, Male, Preventive Health Services, Primary Prevention, Research Design, Risk Factors, Meta-Analysis as Topic, Cognitive Behavioral Therapy, Incidence, Randomized Controlled Trials as Topic, Patient Selection

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