Multimodal emotion perception in young and elderly patients with multiple sclerosis
Bibliographic record
Abstract
Background. Studies suggest that emotion recognition and empathy are impaired in patients with MS (pwMS). Nonetheless, most studies of emotion recognition have used facial stimuli, are restricted to young samples, and rely self-report assessments of empathy. The aims of this study are to determine the impact of MS and age on multimodal emotion recognition (facial emotions and vocal emotional bursts) and on socioemotional sensitivity (as reported by the participants and their informants). We also aim to investigate the associations between emotion recognition, socioemotional sensitivity, and cognitive measures. Methods. We recruited 13 young healthy controls (HC), 14 young pwMS, 14 elderly HC and 15 elderly pwMS. They underwent a short neuropsychological battery, an experimental emotion recognition task including facial emotions and vocal emotional bursts. Both participants and their study informants completed the Revised-Self Monitoring Scale (RSMS) to assess the participant’s socioemotional sensitivity. Results. There was a significant effect of age and group on recognition of both facial emotions and emotional vocal bursts, HC performing significantly better than pwMS, and young participants performing better than elderly participants (no interaction effect). The same effects were observed on self-reported socioemotional sensitivity. However, lower socioemotional sensitivity in pwMS was not reported by the informants. Finally, multimodal emotion recognition did not correlate with socioemotional sensitivity, but it correlated with global cognitive severity. Conclusion. PwMS present with multimodal emotion perception deficits. Our results extend previous findings of decreased emotion perception and empathy to a group of elderly pwMS, in which advancing age does not accentuate these deficits. However, the decreased socioemotional sensitivity reported by pwMS does not appear to be observed by their relatives, nor to correlate with their emotion perception impairments. Future studies should investigate the real-life impacts of emotion perception deficits 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 | 0.001 |
| 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 | 0.000 |
| 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".