Predicting Response to Pro‐Cognitive Interventions in Mood Disorders: A Systematic Review by the International Society for Bipolar Disorders Targeting Cognition Task Force
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".