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Record W3132132626 · doi:10.1080/21678421.2021.1883665

Persian adaptation of Edinburgh Cognitive and Behavioural Screen (ECAS)

2021· article· en· W3132132626 on OpenAlexaboutno aff
Helia Mojtabavi, Shahriar Nafissi, Behrooz Mahmoodi‐Bakhtiari, Davood Fathi, Farzad Fatehi

Bibliographic record

VenueAmyotrophic Lateral Sclerosis and Frontotemporal Degeneration · 2021
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsPersianCognitionNeuropsychologyPopulationClinical psychologyMedicineMontreal Cognitive AssessmentPsychologyCognitive impairmentAudiologyPsychiatry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.052
GPT teacher head0.273
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAmyotrophic Lateral Sclerosis and Frontotemporal DegenerationSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207