Bilingualism, executive control, and age at diagnosis among people with early‐stage <scp>A</scp> lzheimer's disease in <scp>W</scp> ales
Bibliographic record
Abstract
The observation of a bilingual advantage in executive control tasks involving inhibition and management of response conflict suggests that being bilingual might contribute to increased cognitive reserve. In support of this, recent evidence indicates that bilinguals develop Alzheimer's disease (AD) later than monolinguals, and may retain an advantage in performance on executive control tasks. We compared age at the time of receiving an AD diagnosis in bilingual Welsh/English speakers (n = 37) and monolingual English speakers (n = 49), and assessed the performance of bilinguals (n = 24) and monolinguals (n = 49) on a range of executive control tasks. There was a non-significant difference in age at the time of diagnosis, with bilinguals being on average 3 years older than monolinguals, but bilinguals were also significantly more cognitively impaired at the time of diagnosis. There were no significant differences between monolinguals and bilinguals in performance on executive function tests, but bilinguals appeared to show relative strengths in the domain of inhibition and response conflict. Bilingual Welsh/English speakers with AD do not show a clear advantage in executive function over monolingual English speakers, but may retain some benefits in inhibition and management of response conflict. There may be a delay in onset of AD in Welsh/English bilinguals, but if so, it is smaller than that found in some other clinical populations. In this Welsh sample, bilinguals with AD came to the attention of services later than monolinguals, and reasons for this pattern could be explored further.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".