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Randomized Controlled Trial
. 2006 Feb 28;141(2):193-200.
doi: 10.1016/j.psychres.2005.04.007. Epub 2006 Feb 2.

Enrolling research subjects from clinical practice: ethical and procedural issues in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial

Affiliations
Randomized Controlled Trial

Enrolling research subjects from clinical practice: ethical and procedural issues in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial

Jonathan E Alpert et al. Psychiatry Res. .

Abstract

The Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial is a multi-site effectiveness study funded by the National Institute of Mental Health (NIMH) with the aim of identifying successful, acceptable and cost-effective treatment strategies for outpatients with unremitted depression. With enrollment of 4,041 adults with major depressive disorder (MDD), it is the largest controlled psychiatric treatment study ever undertaken. In the course of developing procedures to ensure that ambitious enrollment goals were met, a number of ethical and practical issues became apparent that underscore the conflicts between effectiveness research and human subject protections. These are delineated as they relate to study design; eligibility criteria; incentives to subjects; investigators and clinical sites; the complementary roles of clinical research coordinators (CRCs) and study clinicians; and recruitment and consent procedures. The STAR*D trial exemplifies the interplay and tension between those strategies that integrate research and clinical aims and roles in the service of enhancing external validity, site participation, and recruitment and retention versus those strategies that differentiate research and clinical treatment in the service of research integrity and human subject protections. We hope that a discussion of these key challenges and dilemmas and how they have been addressed will help inform future discussions concerning design and conduct of ethical effectiveness trials designed to optimize care in real world clinical settings.

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