Persian adaptation of Edinburgh Cognitive and Behavioural Screen (ECAS)
Bibliographic record
Abstract
Objectives: To adapt the Edinburgh Cognitive and Behavioral screen (ECAS) English version into Persian. Methods: The ECAS test was adapted and implemented to 30 ALS patients and 31 healthy volunteers in Tehran, Iran. The ECAS results were compared to MoCA and ALS-FRS-r, the other standard tools to determine whether the translated version is reliable and valid in the new language. In addition, the patients’ caregivers were interviewed for behavioral and psychiatric changes. Results: The Persian version of ECAS revealed high internal consistency (α = 0.791), alongside the strong correlation of ECAS and its subscales with MoCA and ALS-FRS. Moreover, Persian ECAS discriminated against the patients and the healthy population well. Sensitivity analysis revealed promising results of Persian ECAS with an area under the curve of 0.871 in ROC curve analysis. Cognitive impairment was observed in 43.33% of patients. Conclusion: The Persian version of the ECAS, exclusively designed for the Iranian population, is the first screening tool to assess multiple neuropsychological functions, which provides a rapid and inclusive screen of cognitive and behavioral impairments specifically in ALS patients.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".