Cognitive Reserve in Parkinson’s Disease: The Effects of Welsh-English Bilingualism on Executive Function
Bibliographic record
Abstract
Objective. Bilingualism has been shown to benefit executive function (EF) and delay the onset of Alzheimer's disease. This study aims at examining whether a bilingual advantage applies to EF in Parkinson's disease (PD). Method. In a cross-sectional outpatient cohort of monolingual English (n = 57) and bilingual Welsh/English (n = 46) speakers with PD we evaluated the effects of bilingualism compared with monolingualism on performance on EF tasks. In bilinguals we also assessed the effects of the degree of daily usage of each language and the degree of bilingualism. Results. Monolinguals showed an advantage in performance of language tests. There were no differences in performance of EF tests in monolinguals and bilinguals. Those who used Welsh less in daily life had better performance on one test of English vocabulary. The degree of bilingualism correlated with one test of nonverbal reasoning and one of working memory but with no other tests of EF. Discussion. The reasons why the expected benefit in EF in Welsh-English bilinguals with PD was not found require further study. Future studies in PD should include other language pairs, analysis of the effects of the degree of bilingualism, and longitudinal analysis of cognitive decline or dementia together with structural or functional neuroimaging.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".