Social cognition in bipolar I and II disorders: an updated systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: In recent years, there has been a rapid increase in reports upon social-cognition impairments in bipolar disorder. This study aimed to compare the characteristics of social cognition domains in bipolar I (BD I) and II (BD II) based on the findings to date. METHODS: A systematic literature search was conducted on Web of Science and PubMed from inception to 28 August 2024. Studies with all-age-group of ICD-10, DSM-IV, DSM-IV-TR, or DSM-5 defined BD (I or II) either in a remitted or symptomatic state were included. The risk of bias was measured using the Newcastle-Ottawa Scale, and the quality of the sources was evaluated using GRADE criteria. Results of the studies were measured by synthesizing Hedge's g effect sizes through a random effects meta-analytic approach. RESULTS: A total of 20 studies were included, covering three core domains of social cognition (theory of mind (ToM), emotion processing and attributions). There was no significant difference in ToM between BD I and BD II and in emotion processing between non-psychotic patients with BD I and BD II, and history of psychosis negatively predicted performance on emotion processing. Furthermore, BD II performed worse than BD I in attributions, with a low to moderate summary effect size. CONCLUSIONS: BD I and BD II performed similarly on ToM and emotional processing, but BD II had more impaired attributions. Future studies are encouraged to control for the influence of clinical features, to use more neuroscientific techniques, and to explore on other domains of social cognition in bipolar subtypes.
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 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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.021 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".