38 Cognitive and Affective Theory of Mind in Young and Elderly Patients with Multiple Sclerosis
Bibliographic record
Abstract
Objective: Theory of mind (ToM) deficits have been reported in patients 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. The aims of this study were to determine the impact of MS and age on cognitive and affective ToM using a more ecological video-based task. We also aimed to investigate the relationships between ToM, cognition and emotion reading to understand the nature of ToM deficits in pwMS. Participants and Methods: 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. 2010). In this task, participants watch four 2-minutes videos of social interactions, which are interrupted by multiple choice questions about either the emotional state (affective ToM; 14 questions) or the intention (cognitive ToM; 14 questions) of the characters. They also underwent a short neuropsychological battery including cognitive tasks (Montreal Cognitive Assessment (MoCA), DKEFS Color-Word Interference Test) and an experimental multimodal emotion recognition task. Results: We found significant effects of group (pwMS < HC), age (older < younger) and condition (cognitive ToM < affective ToM) on the ToM task. Although no interaction effect was found, the elderly pwMS group showed the largest discrepancy between their cognitive and affective ToM, the cognitive subtask being significantly more affected. ToM significantly correlated with general cognition (MoCA) in all participants, while cognitive inhibition (DKEFS Color-Word Interference Test) correlated with ToM only in elderly pwMS. No significant correlation was observed between ToM and emotion reading. Conclusions: This study highlights both cognitive and affective ToM deficits in pwMS, and particularly in cognitive ToM in elderly pwMS. These impairments could be underlied by cognitive and executive difficulties, but not by core social cognitive impairments, as observed in the correlation analyses. Future studies should investigate the relationships between ToM impairments and impairments in real-life empathy and social behavior 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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".