Personality in Autism Spectrum Disorder: Associations With Face Memory Deficit and Theory of Mind
Bibliographic record
Abstract
OBJECTIVE: To examine the personality profiles of adults with autism spectrum disorder (ASD) using a standard personality assessment and to investigate the association between personality, ASD-related face memory deficit (FMD), and theory of mind (ToM). In a broader context, to examine whether there are distinct clinical phenotypes in the ASD population that have implications for personality development and treatment. METHOD: Fifty-five adults with ASD and 22 neurotypical (NT) adults underwent a battery of neuropsychological tests, including measures of personality, face memory, and ToM. We compared ASD and NT groups in terms of their Personality Assessment Inventory (PAI) profiles. Additional analyses focused on the association between specific PAI scales and FMD. Performance on the Eyes Test was compared across groups and was examined in relation to FMD. RESULTS: Adults with ASD demonstrated significant elevations on several PAI scales compared with NT adults. The presence of FMD was associated with differing PAI profiles among the ASD adults. The ASD adults with FMD scored significantly higher on scales that are sensitive to positive impression management and treatment rejection and significantly lower on scales that are sensitive to borderline personality, anxiety, depression, schizophrenia, and stress. There was a significant association between performance on the Eyes Test and FMD in the ASD group. CONCLUSION: Adults with ASD have a unique personality profile. Further, ASD adults with FMD have reduced insight into their difficulties with emotional processing and may not be as sensitive as ASD adults without FMD to the emotions of others.
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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) | 0.001 | 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".