Sentence processing in high proficient Kannada–English bilinguals: a reaction time study

Ravi, Sunil Kumar; Chengappa, Shyamala

doi:10.1080/14790718.2014.964248

Cited by 2 publications

(2 citation statements)

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“…Statistical analyses were performed using R Studio (v2023.06.0, build 421). The weighted average of data across the six centers in the US validation study 18 was used to compare with the data from the Indian sample. Independent samples t-tests were used to examine group differences between the US and Indian samples for age, education, age at seizure onset, and duration of epilepsy.…”

Section: Discussionmentioning

confidence: 99%

“…For tests relying on linguistic abilities (naming, semantic, and phonemic fluency tests), the participants were allowed to freely switch between languages, as restricting this can sometimes adversely affect performance. 17,18 In India, multilingual patients are permitted to provide responses in whatever language they choose for the naming and verbal fluency tests. This approach has been recommended by a consortium of experts and is regarded as more ecologically valid and consistent with the practice of multilingualism in India.…”

Section: Methodsmentioning

confidence: 99%

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Cross‐cultural application of the International Classification of Cognitive Disorders in Epilepsy (IC‐CoDE)

Shah,

Rajeshree,

Sahu

et al. 2024

Epilepsia

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ObjectiveEfforts to understand the global variability in cognitive profiles in patients with epilepsy have been stymied by the lack of a standardized diagnostic system. This study examined the cross‐cultural applicability of the International Classification of Cognitive Disorders in Epilepsy (IC‐CoDE) in a cohort of patients with temporal lobe epilepsy (TLE) in India that was diverse in language, education, and cultural background.MethodsA cohort of 548 adults with TLE from Mumbai completed a presurgical comprehensive neuropsychological evaluation. The IC‐CoDE taxonomy was applied to derive cognitive phenotypes in the sample. Analyses of variance were conducted to examine differences in demographic and clinical characteristics across the phenotypes, and chi‐squared tests were used to determine whether the phenotype distribution differed between the Mumbai sample and published data from a multicenter US sample.ResultsUsing the IC‐CoDE criteria, 47% of our cohort showed an intact cognitive profile, 31% a single‐domain impairment, 16% a bidomain impairment, and 6% a generalized impairment profile. The distribution of cognitive phenotypes was similar between the Indian and US cohorts for the intact and bidomain phenotypes, but differed for the single and generalized domains. There was a larger proportion of patients with single‐domain impairment in the Indian cohort and a larger proportion with generalized impairment in the US cohort. Among patients with single‐domain impairment, a greater proportion exhibited memory impairment in the Indian cohort, whereas a greater proportion showed language impairment in the US sample, likely reflecting differences in language administration procedures and sample characteristics including a higher rate of mesial temporal sclerosis in the Indian sample.SignificanceOur results demonstrate the applicability of IC‐CoDE in a group of culturally and linguistically diverse patients from India. This approach enhances our understanding of cognitive variability across cultures and enables harmonized and inclusive research into the neuropsychological aspects of epilepsy.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%