Identifying social cognition subgroups in euthymic patients with bipolar disorder: a cluster analytical approach
Bibliographic record
Abstract
BACKGROUND: Bipolar disorder (BD) is associated with social cognition (SC) impairments even during remission periods although a large heterogeneity has been described. Our aim was to explore the existence of different profiles on SC in euthymic patients with BD, and further explore the potential impact of distinct variables on SC. METHODS: Hierarchical cluster analysis was conducted using three SC domains [Theory of Mind (ToM), Emotional Intelligence (EI) and Attributional Bias (AB)]. The sample comprised of 131 individuals, 71 patients with BD and 60 healthy control subjects who were compared in terms of SC performance, demographic, clinical, and neurocognitive variables. A logistic regression model was used to estimate the effect of SC-associated risk factors. RESULTS: = 23, 32.4%) with mild deficits in ToM and AB domains and with moderate difficulties in EI. Patients with low SC performance were mostly males, showed lower estimated IQ, higher subthreshold depressive symptoms, longer illness duration, and poorer visual memory and attention. Low estimated IQ (OR 0.920, 95% CI 0.863-0.981), male gender (OR 5.661, 95% CI 1.473-21.762), and longer illness duration (OR 1.085, 95% CI 1.006-1.171) contributed the most to the patients clustering. The model explained up to 35% of the variance in SC performance. CONCLUSIONS: Our results confirmed the existence of two discrete profiles of SC among BD. Nearly two-thirds of patients exhibited adjusted social cognitive abilities. Longer illness duration, male gender, and lower estimated IQ were associated with low SC performance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".