SYSTEMATIC REVIEW article
Front. Psychiatry
Sec. Public Mental Health
Algorithm-guided treatment for major depressive disorder versus treatment as usual: a systematic review
Deni Rkman 1,2
René Ernst Nielsen 1,2
Rasmus Wentzer Licht 1,2
Klaus Martiny 3,4
Philipp Ritter 5,6
Marton Asztalos 1,2
1. Department of Psychiatry, Aalborg University Hospital, Aalborg, Denmark
2. Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
3. Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
4. Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, Copenhagen, Denmark
5. Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technical University Dresden, Dresden, Germany
6. Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
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Abstract
A substantial proportion of patients with major depressive disorder do not remit after the initial pharmacological treatment, and a major obstacle is that progression to subsequent treatment steps often occurs too slowly, highlighting the need for more structured and effective therapeutic strategies. Algorithm-guided treatments (AGTs) provide a systematic, stepwise framework for clinical decision-making, potentially improving acute treatment outcomes compared to treatment as usual (TAU). This systematic review, conducted according to PRISMA 2020 guidelines, evaluated randomized controlled trials (RCTs) comparing AGTs to TAU in adult patients with major depressive disorder. Databases searched included PubMed, Scopus, Embase, PsychInfo, and the Cochrane Library up to June 2025. Trials investigating adults diagnosed with major depressive disorder, utilizing clinician-rated depression scales, and with trial duration of four weeks or more were included. Seven RCTs met the This is a provisional file, not the final typeset article criteria, encompassing over 3,500 participants. Most studies demonstrated superior outcomes in participants allocated to AGT – compared to TAU, including significantly shorter time to remission, higher rates of proportion of patients with remission and response, as well as and better adherence to treatment protocols. Some studies found marginal or nonsignificant differences between interventions in some of the outcomes, particularly those involving comorbid populations. These findings suggest that implementing structured, algorithm-based treatment strategies can improve the quality and efficacy of care for patients diagnosed with major depressive disorder, supporting their wider integration into clinical practice.
Summary
Keywords
algorithm-guided treatment1, depression3, major depressivedisorder4, measurement-based care5, Systematic review6, treatment as usua2
Received
10 December 2025
Accepted
16 February 2026
Copyright
© 2026 Rkman, Ernst Nielsen, Licht, Martiny, Ritter and Asztalos. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Marton Asztalos
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.