PLoS ONE (Jan 2022)

Using big data to understand bilingual performance in semantic fluency: Findings from the Canadian Longitudinal Study on Aging

  • Vanessa Taler,
  • Brendan Johns

Journal volume & issue
Vol. 17, no. 11

Abstract

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Objectives This study aimed to characterize verbal fluency performance in monolinguals and bilinguals using data from the Canadian Longitudinal Study on Aging (CLSA). Methods A large sample of adults aged 45–85 (n = 12,875) completed a one-minute animal fluency task in English. Participants were English-speaking monolinguals (n = 9,759), bilinguals who spoke English as their first language (L1 bilinguals, n = 1,836), and bilinguals who spoke English as their second language (L2 bilinguals, n = 1,280). Using a distributional modeling approach to quantify the semantic similarity of words, we examined the impact of word frequency and pairwise semantic similarity on performance on this task. Results Overall, L1 bilinguals outperformed monolinguals on the verbal fluency task: they produced more items, and these items were of lower average frequency and semantic similarity. Monolinguals in turn outperformed L2 bilinguals on these measures. The results held across different age groups, educational, and income levels. Discussion These results demonstrate an advantage for bilinguals compared to monolinguals on a category fluency task, when performed in the first language, indicating that, at least in the CLSA sample, bilinguals have superior semantic search capabilities in their first language compared to monolingual speakers of that language.