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Record W4410371652 · doi:10.1192/bjp.2025.56

Psychological intervention in individuals with subthreshold depression: individual participant data meta-analysis of treatment effects and moderators

2025· review· en· W4410371652 on OpenAlexaff
Mathias Harrer, Antonia A Sprenger, Susan Illing, Marcel C. Adriaanse, Steven M. Albert, Esther Allart, Osvaldo P. Almeida, Julian Basanovic, K.M.P. van Bastelaar, Philip J. Batterham, Harald Baumeister, Thomas Berger, Vanessa Blanco, Ragnhild Bø, Robin J. Casten, Dicken Chan, Helen Christensen, Markéta Čihařová, Lorna Cook, John E. Cornell, Elysia Poggi Davis, Keith S. Dobson, Els Dozeman, Simon Gilbody, Benjamin L. Hankin, Rimke Haringsma, Kristof Hoorelbeke, Michael R. Irwin, Femke Jansen, Rune Jonassen, Eirini Karyotaki, Norito Kawakami, Jan Philipp Klein, Candace Konnert, Kotaro Imamura, Nils Inge Landrø, Ma. Asunción Lara, Huynh Nhu Le, Dirk Lehr, Juan V. Luciano, Steffen Moritz, Jana Mossey, Ricardo F. Muñoz, Anna Muntingh, Stephanie Nobis, Richard Olmstead, Patricia Otero, Mirjana Pibernik-Okanović, Anne Margriet Pot, Charles F. Reynolds, Barry W. Rovner, Juan P. Sanabria‐Mazo, Lasse Sander, Filip Smit, Frank J. Snoek, Viola Spek, Philip Spinhoven, Liza Stelmach, Yannik Terhorst, Fernando L. Vázquez, Irma M. Verdonck‐de Leeuw, Edward Watkins, Wenhui Yang, Samuel Yeung Shan Wong, Johannes Zimmermann, Masatsugu Sakata, Toshi A. Furukawa, Stefan Leucht, Pim Cuijpers, Claudia Buntrock, David Daniel Ebert

Bibliographic record

VenueThe British Journal of Psychiatry · 2025
Typereview
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsCARE CanadaUniversity of Calgary
FundersDaiichi Sankyo EuropeSanofiNovo NordiskShionogiBundesministerium für GesundheitServier
KeywordsDepression (economics)Meta-analysisRelative riskIntervention (counseling)Clinical psychologyAnxietyMedicineRandomized controlled trialPsychologyPsychiatryInternal medicineConfidence interval

Abstract

fetched live from OpenAlex

Background It remains unclear which individuals with subthreshold depression benefit most from psychological intervention, and what long-term effects this has on symptom deterioration, response and remission. Aims To synthesise psychological intervention benefits in adults with subthreshold depression up to 2 years, and explore participant-level effect-modifiers. Method Randomised trials comparing psychological intervention with inactive control were identified via systematic search. Authors were contacted to obtain individual participant data (IPD), analysed using Bayesian one-stage meta-analysis. Treatment–covariate interactions were added to examine moderators. Hierarchical-additive models were used to explore treatment benefits conditional on baseline Patient Health Questionnaire 9 (PHQ-9) values. Results IPD of 10 671 individuals (50 studies) could be included. We found significant effects on depressive symptom severity up to 12 months (standardised mean-difference [s.m.d.] = −0.48 to −0.27). Effects could not be ascertained up to 24 months (s.m.d. = −0.18). Similar findings emerged for 50% symptom reduction (relative risk = 1.27–2.79), reliable improvement (relative risk = 1.38–3.17), deterioration (relative risk = 0.67–0.54) and close-to-symptom-free status (relative risk = 1.41–2.80). Among participant-level moderators, only initial depression and anxiety severity were highly credible ( P > 0.99). Predicted treatment benefits decreased with lower symptom severity but remained minimally important even for very mild symptoms (s.m.d. = −0.33 for PHQ-9 = 5). Conclusions Psychological intervention reduces the symptom burden in individuals with subthreshold depression up to 1 year, and protects against symptom deterioration. Benefits up to 2 years are less certain. We find strong support for intervention in subthreshold depression, particularly with PHQ-9 scores ≥ 10. For very mild symptoms, scalable treatments could be an attractive option.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.603
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.175
GPT teacher head0.418
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2025
Admission routes1
Has abstractyes

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