Randomised controlled cognition trials in remitted patients with mood disorders published between 2015 and 2021: A systematic review by the International Society for Bipolar Disorders Targeting Cognition Task Force
Bibliographic record
Abstract
BACKGROUND: Cognitive impairments are an emerging treatment target in mood disorders, but currently there are no evidence-based pro-cognitive treatments indicated for patients in remission. With this systematic review of randomised controlled trials (RCTs), the International Society for Bipolar Disorders (ISBD) Targeting Cognition Task force provides an update of the most promising treatments and methodological recommendations. METHODS: The review included RCTs of candidate pro-cognitive interventions in fully or partially remitted patients with major depressive disorder or bipolar disorder. We followed the procedures of the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) 2020 statement. Searches were conducted on PubMed/MEDLINE, PsycInfo, EMBASE and Cochrane Library from January 2015, when two prior systematic reviews were conducted, until February 2021. Two independent authors reviewed the studies with the Revised Cochrane Collaboration's Risk of Bias tool for Randomised trials. RESULTS: We identified 16 RCTs (N = 859) investigating cognitive remediation (CR; k = 6; N = 311), direct current or repetitive magnetic stimulation (k = 3; N = 127), or pharmacological interventions (k = 7; N = 421). CR showed most consistent cognitive benefits, with two trials showing improvements on primary outcomes. Neuromodulatory interventions revealed no clear efficacy. Among pharmacological interventions, modafinil and lurasidone showed early positive results. Sources of bias included small samples, lack of pre-screening for objective cognitive impairment, no primary outcome and no information on allocation sequence masking. CONCLUSIONS: Evidence for pro-cognitive treatments in mood disorders is emerging. Recommendations are to increase sample sizes, pre-screen for impairment in targeted domain(s), select one primary outcome, aid transfer to real-world functioning, investigate multimodal interventions and include neuroimaging.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.017 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".