Alexithymia predicts face emotion perception after acquired brain injury
Bibliographic record
Abstract
BACKGROUND: This study investigated the presence and level of alexithymia and examined the relationship between alexithymia and affect recognition abilities after acquired brain injury (ABI), accounting separately for etiology due to stroke or traumatic brain injury (TBI). METHODS: Ninety-nine neurologically healthy adults (NHA) and 119 adults with moderate-to-severe ABI (63 TBI, 56 stroke) participated. Main measures included the Toronto Alexithymia Scale-20 (TAS-20) and Multicultural Facial Emotion Perception Test (MFEPT). RESULTS: ABI groups endorsed greater alexithymia than NHA, but TBI and stroke subgroups did not significantly differ. Hierarchical multiple regression indicated that TAS-20 subscales difficulty identifying feelings (DIF) and externally oriented thinking (EOT), but not Difficulty Describing Feelings (DDF), added unique value to predicting objective affect recognition (MFEPT) after accounting for age, education, sex, face recognition ability, and general cognitive function. Moreover, the relationship between alexithymia and affect recognition was moderated by group: DIF and DDF were inversely related to MFEPT only for adults with ABI. EOT was inversely related to affect recognition for all three groups. CONCLUSIONS: Adults with ABI experience alexithymia more frequently and intensely than neurologically healthy adults, and this impairment may partly underlie struggles with affective processing frequently observed in these individuals on experimental tasks and in real-world interactions.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".