Facial emotion recognition and empathy for pain in patients with type 2 diabetes mellitus
Bibliographic record
Abstract
Objective: Type 2 diabetes mellitus (T2DM) is associated with cognitive decline, but its impact on social cognition remains poorly understood. This study investigated whether individuals with T2DM exhibit impairments in facial emotion recognition and empathy for pain, two domains crucial for daily interpersonal functioning that are often overlooked in neuropsychological assessments. Method: Seventy-six participants (37 with T2DM and 39 matched healthy controls) completed two validated social cognition tasks: a dynamic Facial Emotion Morphing Test and an empathy-for-pain task involving 25 animated scenarios (intentional, accidental, and neutral harm). Groups were matched for age, sex, and education. Analyses of covariance were conducted using Montreal Cognitive Assessment (MoCA) scores as covariates to control for global cognitive status. Results: Compared to controls, individuals with T2DM showed significantly lower overall emotion recognition accuracy (ηp2 = 0.10) and fear recognition accuracy (ηp2 = 0.06). In the empathy-for-pain task, they exhibited reduced intentionality comprehension (ηp2 = 0.05, d = 0.73), increased attribution of harmful intent (ηp2 = 0.05, d = −0.60), and harsher punishment judgments (ηp2 = 0.08). These effects were of medium magnitude and were not explained by demographic, cognitive, or clinical factors. Conclusions: T2DM is associated with selective impairments in social cognition, even in the absence of global cognitive decline. These findings underscore the clinical utility of assessing social cognition in patients with T2DM, as such deficits may compromise interpersonal functioning and quality of life. Incorporating ecologically valid social cognition measures into neuropsychological evaluations may support early detection of brain dysfunction in metabolic conditions and inform interventions aimed at preserving social cognitive health.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".