MétaCan
Menu
Back to cohort
Record W4415178429 · doi:10.1111/acps.70038

Predicting Response to Pro‐Cognitive Interventions in Mood Disorders: A Systematic Review by the International Society for Bipolar Disorders Targeting Cognition Task Force

2025· review· en· W4415178429 on OpenAlexafffund
Dimosthenis Tsapekos, Michail Kalfas, Johanna Mariegaard Schandorff, Caterina del Mar Bonnín, Christopher R. Bowie, Vicent Balanzá‐Martínez, Katherine E. Burdick, André F. Carvalho, Annemiek Dols, Katie M. Douglas, Peter Gallagher, Gregor Hasler, Lars Vedel Kessing, Hanne Lie Kjærstad, Beny Lafer, Kathryn E. Lewandowski, Carlos López‐Jaramillo, Anabel Martínez‐Arán, Roger S. McIntyre, Richard Porter, Scot E. Purdon, Ayal Schaffer, Paul Stokes, Tomiki Sumiyoshi, Ivan J. Torres, Tamsyn E. Van Rheenen, Lakshmi N. Yatham, Jeff Zarp Petersen, Allan H. Young, Eduard Vieta, Kamilla Woznica Miskowiak

Bibliographic record

VenueActa Psychiatrica Scandinavica · 2025
Typereview
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsUniversity of AlbertaUniversity of TorontoUniversity of British ColumbiaQueen's University
FundersJanssen Research and DevelopmentCanadian Institutes of Health ResearchSanofiSouth London and Maudsley NHS Foundation TrustNIHR Maudsley Biomedical Research CentreAllerganIdorsia PharmaceuticalsBausch HealthSunovionH. Lundbeck A/SServierKing's Health PartnersEisaiNational Natural Science Foundation of ChinaKing's College LondonMedical Research CouncilTeva Pharmaceutical IndustriesDepartment of Health and Social CarePurdue UniversityNovo NordiskNational Institute for Health and Care ResearchDainippon Sumitomo PharmaBiogenPfizerInternational Society for Bipolar DisordersGedeon Richter
KeywordsCognitionMoodPsychological interventionReplicateMood disordersTask (project management)

Abstract

fetched live from OpenAlex

INTRODUCTION: Major depressive disorder (MDD) and bipolar disorder (BD) are often associated with persistent cognitive deficits that impair psychosocial functioning. While pro-cognitive interventions show promise, trial findings are inconsistent, potentially due to baseline factors influencing treatment response. This systematic review summarizes evidence on pre-treatment characteristics associated with cognitive improvement and offers methodological recommendations. METHODS: A systematic search was conducted in PubMed/MEDLINE, EMBASE, PsycINFO, and Cochrane Library from inception to February 28, 2025. Eligible studies included primary or secondary analyses of randomized controlled trials (RCTs) investigating predictors of cognitive response to pro-cognitive interventions in MDD and/or BD. Two researchers independently conducted study selection and risk of bias assessments. Findings were synthesized qualitatively. RESULTS: Forty studies (N = 3864) were identified, covering pharmacological treatments (k = 20; N = 2299), psychological therapies (k = 16; N = 1165), brain stimulation (k = 2; N = 168), and physical activity (k = 2; N = 232). Poorer baseline cognitive performance was the most consistent predictor of greater cognitive improvement, though the direction of the effect was not entirely uniform across all studies. Baseline depression severity showed no significant association with cognitive outcomes. Age, education, sex, IQ, diagnosis, and medication status were similarly non-predictive. Risk of bias was high in 77% of studies, mainly due to deviations from specified outcomes, poor randomization processes, and inconsistent handling of missing data. Considerable heterogeneity in interventions, outcome measures, and sample characteristics limited replicability and precluded meta-analysis. CONCLUSION: Poorer baseline cognition emerged as the most reliable predictor of greater cognitive improvement across interventions. More rigorous, well-powered studies are needed to replicate these findings and identify robust predictors to guide personalized pro-cognitive treatment approaches in mood disorders.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.214
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.002
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 head0.020
GPT teacher head0.348
Teacher spread0.328 · 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.

Study designSystematic review
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

Citations2
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueActa Psychiatrica ScandinavicaSame topicBipolar Disorder and TreatmentFrench-language works237,207