Study of Prosodic Skills of Persian-Speaking Adults with Autism Spectrum Disorder Based on the Persian Version of Montreal Protocol for the Evaluation of Communication (P.M.E.C.)
Bibliographic record
Abstract
Background: Research indicates that individuals with autism spectrum disorder (ASD) often struggle with prosodic skills, which include the rhythm, stress, and intonation of speech. While most studies focus on children, some findings suggest these challenges persist into adulthood. Methods: This comparative cross-sectional study used a quantitative approach to assess prosodic impairments in Persian-speaking adults with ASD. Thirteen Persian-speaking men with autism, aged 25 to 44 (mean = 32.84, SD = 4.17), participated. Their educational backgrounds ranged from third grade to 20 years of formal education. A control group of 26 healthy Persian-speaking men matched in age and education was also included. Prosodic skills were evaluated using five subtests from the Persian version of the Montreal Protocol for the Evaluation of Communication (P.M.E.C.): linguistic prosody comprehension, linguistic prosody repetition, emotional prosody comprehension, emotional prosody repetition, and emotional prosody production. Data were analyzed using descriptive statistics, independent samples t-tests, and the Kolmogorov-Smirnov test. Results: Participants with ASD performed significantly worse than the control group across all five subtests. Significant differences were found in linguistic prosody comprehension (p = 0.002), linguistic prosody repetition (p = 0.0001), emotional prosody comprehension (p = 0.004), emotional prosody repetition (p = 0.015), and emotional prosody production (p = 0.0001). These results highlight substantial deficits in both linguistic and emotional prosody among adults with ASD. Conclusion: This study emphasizes the need for targeted assessment and intervention strategies for prosodic impairments in adults with autism. The findings have practical implications for clinical, educational, and research settings.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".