Cognitive and affective theory of mind in young and elderly patients with multiple sclerosis
Bibliographic record
Abstract
Theory of mind (ToM) deficits have been reported in persons with multiple sclerosis (pwMS). However, most studies have used pictures or written scenarios as stimuli without distinguishing between cognitive and affective ToM, and no studies have investigated older pwMS. We recruited 13 young healthy controls (HC), 14 young pwMS, 14 elderly HC and 15 elderly pwMS. ToM was measured using an adaptation of the Conversations and Insinuations task (Ouellet et al., J. Int. Neuropsychol. Soc., 16, 2010, 287). In this ecological video-based task, participants watch four 2-minute videos of social interactions, which are interrupted by multiple choice questions about either the emotional state (affective ToM) or the intention (cognitive ToM) of the characters. They also underwent a short neuropsychological battery including cognitive, executive and social cognition tasks and questionnaires. We observed a significant interaction between the ToM conditions and the groups regarding ToM performance. Elderly pwMS scored significantly lower than elderly HC and young pwMS in cognitive ToM, but not in affective ToM. They also showed the largest discrepancy between their cognitive and affective ToM. Young pwMS showed relatively preserved ToM in both conditions. Both cognitive and affective ToM correlated with global cognition and executive abilities, but not with social cognitive measures (emotion recognition, real-life empathy). This study suggests that decline in cognitive ToM might be accentuated by advancing age in pwMS. These impairments are most likely underlied by cognitive and executive difficulties, but not by core social cognitive impairments. Future studies should investigate the real-life impacts of ToM impairments in pwMS.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".