Evidence map›Paper›PMID 42805662›Full record

ArticleBMJ open2026

Why did antidepressant deprescribing fail? A scoping review of contributing factors.

Eiya Ayed, Erwin Gerard, Paul Quindroit, Carla Di Martino, Antoine Lamer, Maxime Bubrovszky, Jan Baran, Matthieu Calafiore, Annie Standaert, Jean-Baptiste Beuscart

Abstract readScoping Review
In one paragraph

Article in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Eiya AyedMETRICS ULR 2694, Universite Lille Nord de France, Lille, France eiya.ayed@univ-lille.fr.ORCID http://orcid.org/0009-0008-6202-1591
Erwin GerardMETRICS ULR 2694, Universite Lille Nord de France, Lille, France.ORCID http://orcid.org/0000-0002-7712-4138
Paul QuindroitMETRICS ULR 2694, Universite Lille Nord de France, Lille, France.ORCID http://orcid.org/0000-0003-0387-2413
Carla Di MartinoMETRICS ULR 2694, Universite Lille Nord de France, Lille, France.ORCID http://orcid.org/0000-0003-1400-4267
Antoine LamerMETRICS ULR 2694, Universite Lille Nord de France, Lille, France.ORCID http://orcid.org/0000-0002-9546-1808
Maxime BubrovszkyFédération Régionale de Recherche en Psychiatrie et Santé Mentale Hauts-de-France, Saint-André-lez-Lille, Nord-Pas-de-Calais-Picardie, France.
Jan BaranUniversite de Lille UFR des Sciences de Sante et du Sport, Lille, Hauts-de-France, France.ORCID http://orcid.org/0009-0004-3005-8147
Matthieu CalafioreMETRICS ULR 2694, Universite Lille Nord de France, Lille, France.ORCID http://orcid.org/0000-0002-4755-5172
Annie StandaertUniversite de Lille UFR des Sciences de Sante et du Sport, Lille, Hauts-de-France, France.ORCID http://orcid.org/0000-0002-7752-3964
Jean-Baptiste BeuscartMETRICS ULR 2694, Universite Lille Nord de France, Lille, France.ORCID http://orcid.org/0000-0002-0734-8371

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAntidepressant use continues to rise in primary care, often beyond recommended durations. Previous reviews have found insufficient evidence to support long-term antidepressant discontinuation compared with maintenance treatment.

objectiveTo describe how antidepressant deprescribing interventions have been designed in primary care and identify features that explore potential reasons for limited effectiveness.

designScoping review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) guidance. DATA SOURCES: PubMed, Web of Science and PsycINFO were searched through August 2025. ELIGIBILITY CRITERIA: We included randomised controlled trials and cohort studies of patients prescribed antidepressants despite the absence of current depressive symptoms. Studies were excluded if they were reviews, protocols, case reports, database studies, editorials or commentaries. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently screened records, with disagreements resolved by a third reviewer. Findings were synthesised descriptively to identify characteristics of study populations, interventions, healthcare professionals and care processes that may help explain the limited effectiveness reported in antidepressant deprescribing trials.

resultsNine studies were included. RCTs mainly enrolled patients with recurrent depression or major depressive disorder and generally used short tapering schedules. General practitioners led most interventions, while other health care professionals were variably involved. No study reported structured interprofessional collaboration, sustained communication between professionals, or patient and public involvement. Across trials, adherence to deprescribing protocols was moderate to low and relapse rates remained high in most studies. The two cohort studies used longer, more gradual, including hyperbolic, tapering strategies and reported higher discontinuation rates.

conclusionThis review identifies population and methodological gaps in antidepressant deprescribing research in primary care. Future studies should include patients with unclear long-term indications or less severe depressive symptoms, use more adaptive tapering strategies and strengthen collaboration between healthcare professionals.

Indexed as

Antidepressive AgentsDeprescriptionsDepressionMajor Depressive DisorderHumansPrimary Health CareRandomized Controlled Trials as TopicAntidepressive AgentsDeprescriptionsDepression & mood disordersGeneral PracticeInterprofessional RelationsPharmacistsPrimary Health Care

Identifiers

PMID42805662
PMCPMC13630028

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.