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How to prove that your therapy is effective, even when it is not: a guideline

Part of: Special Articles

Published online by Cambridge University Press:  28 September 2015

P. Cuijpers  and
I. A. Cristea
P. Cuijpers*
Affiliation:
Department of Clinical Psychology, VU University Amsterdam, The Netherlands EMGO Institute for Health and Care Research, The Netherlands
I. A. Cristea
Affiliation:
Department of Clinical Psychology and Psychotherapy, Babeş-Bolyai University, Cluj-Napoca, Romania Clinical Psychology Branch, Department of Surgical, Medical, Molecular and Critical Pathology, University of Pisa, Pisa, Italy
*
*Address for correspondence: P. Cuijpers, Professor of Clinical Psychology, Department of Clinical Psychology, VU University Amsterdam, Van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands. (Email: [email protected])
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Abstract

Aims.

Suppose you are the developer of a new therapy for a mental health problem or you have several years of experience working with such a therapy, and you would like to prove that it is effective. Randomised trials have become the gold standard to prove that interventions are effective, and they are used by treatment guidelines and policy makers to decide whether or not to adopt, implement or fund a therapy.

Methods.

You would want to do such a randomised trial to get your therapy disseminated, but in reality your clinical experience already showed you that the therapy works. How could you do a trial in order to optimise the chance of finding a positive effect?

Results.

Methods that can help include a strong allegiance towards the therapy, anything that increases expectations and hope in participants, making use of the weak spots of randomised trials (risk of bias), small sample sizes and waiting list control groups (but not comparisons with existing interventions). And if all that fails one can always not publish the outcomes and wait for positive trials.

Conclusions.

Several methods are available to help you show that your therapy is effective, even when it is not.

Keywords

Control groupsrandomised trialresearcher allegiancerisk of bias
Type
Special Article
Information
Epidemiology and Psychiatric Sciences , Volume 25 , Issue 5 , October 2016 , pp. 428 - 435
Copyright
Copyright © Cambridge University Press 2015 

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