Deficits of social cognition in bipolar disorder: Systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: The association between impaired social cognition and bipolar disorder (BD) is well established. However, to our knowledge, there has not been a recent systematic review that characterizes disparate dimensions of social cognition in BD. Herein, this systematic review and meta-analysis aimed to synthesize the literature on core aspects of social cognition (i.e., Theory of Mind, emotion recognition, and social judgment) to identify potential areas of impairment. METHODS: Online databases (i.e., PubMed, Cochrane Libraries, PsycINFO) and Google Scholar were searched from inception to May 2021. Studies with populations ages ≥16 with DSM-IV or DSM-5 defined BD (I or II) either in a euthymic or symptomatic state were included. The risk of bias was measured using the ROBINS-1 tool, and the quality of the sources was evaluated using GRADE criteria. The results of the studies were quantitatively measured by synthesizing Hedge's g effect sizes through a random effects meta-analytic approach. RESULTS: A total of 29 studies were included in the final review (i.e., 12 studies on the Theory of Mind, 11 on emotion recognition, and 6 on social judgment). Overall, results demonstrated social cognition to be moderately impaired in individuals with BD (d = 0.59). The individual domains ranged in effect size (0.38 < d < 0.70), providing evidence for variation in impairment within social cognition. DISCUSSION: Individuals with BD exhibit clinically significant deficits in social cognition during euthymic and symptomatic states. Social cognition impairments in individuals with BD are an important therapeutic target for treatment discovery and development.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.020 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".