Lexical access in a bilingual speaker with dementia: Changes over time

ABSTRACT

In this article, we explore the naming skills of a bilingual English-Norwegian speaker diagnosed with Primary Progressive Aphasia, in each of his languages across three different speech contexts: confrontation naming, semi-spontaneous narrative (picture description), and conversation, and at two points in time: 12 and 30 months post diagnosis, respectively. The results are discussed in light of two main theories of lexical retrieval in healthy, elderly speakers: the Transmission Deficit Hypothesis and the Inhibitory Deficit Theory. Our data show that, consistent with the participant’s premorbid use of and proficiency in the two languages, his performance in his L2 is lower than in his L1, but this difference diminishes as the disease progresses. This is the case across the three speech contexts; however, the difference is smaller in the narrative task, where his performance is very low in both languages already at the first measurement point. Despite his word finding problems, he is able to take active part in conversation, particularly in his L1 and more so at the first measurement point. In addition to the task effect, we find effects of word class, frequency, and cognateness on his naming skills. His performance seems to support the Transmission Deficit Hypothesis. By combining different tools and methods of analysis, we get a more comprehensive picture of the impact of the dementia on the speaker’s languages from an intra-individual as well as an inter-individual perspective, which may be useful in research as well as in clinical practice.

KEYWORDS:

• Bilingualism
• dementia
• lexical access
• longitudinal study
• primary progressive aphasia

View correction statement:

Correction to: Lind, Simonsen, Bjønness Ribu, Svendsen, Svennevig, and de Bot, Lexical access in a bilingual speaker with dementia: Changes over time

Acknowledgements

We thank JJ and his wife for participating in this study, Malene Bøyum and Gözde Mercan for assistance with the data collection, and Pernille Hansen for help with the statistical analyses.

Declaration of interest

The authors report no conflicts of interest.

Funding

This work was supported by The Research Council of Norway [223265 and 250093].

Notes

¹ We use the term bilingual in the broad sense, referring to speakers of two or more languages.

² None of these studies include bilingual participants.

³ For practical purposes, we had to use the same test administrator for both sessions, and this is of course unfortunate with regard to creating a monolingual condition. However, it is well-known that a great majority of the adult population in Norway, particularly those with a higher, academic education, understands and speaks English reasonably well, so completely monolingual settings are generally less likely when the languages in question are Norwegian and English.

⁴ The full test is available from https://www.health.qld.gov.au/tpch/html/rudas. In a systematic review and meta-analysis with data from 1236 participants, Naqvi, Haider, Tomlinson, and Alibhai (2015) found a pooled sensitivity of 77.2% and a pooled specificity of 85.9% for RUDAS. A pooled estimate of the correlation between RUDAS and MMSE was 0.77, and scores on RUDAS were less affected by language and education level than scores on MMSE. They concluded that RUDAS is an assessment tool that ‘has shown strong psychometric properties in several countries [and] shows particular advantage in culturally and linguistically diverse populations’ (Naqvi et al., 2015: E175). Our reason for using RUDAS was that this case study is a pilot for a larger study of bilinguals with dementia, including participants from different countries and with low levels of education.

⁵ Psychology Software Tools, Inc. [E-Prime 2.0]. (2012). Retrieved from http://www.pstnet.com.

⁶ Z-scores are calculated based on estimates of averages published in the MOANS age-corrected scaled scores (Ivnik et al., 1996).

⁷ JJ was unable to complete TMT-B at time of diagnosis, and following scoring criteria his time was recorded as 301 seconds.

⁸ JJ’s wife was not instructed to evaluate his communication skills in just one of his languages exclusively, as the CETI is not linked to any specific language, but rather to functional, verbal communication in general. It is possible that the scores would have been different if she had been asked to evaluate his functional communication in his L1 separately from his L2 and vice versa.

⁹ Both of these tests originally comprise 40 items, and norms based on healthy, monolingual speakers for the full versions of the tests show high average scores (98% on both tests).

¹⁰ Auxiliaries and semantically light verbs were not included in the calculation of lexical density since they are best regarded as function words and not content words (Malvern, Richards, Chipere, & Durán, 2004).

¹¹ Since we only had audiotaped data, non-verbal behaviour was obviously not taken into account.

¹² In the excerpts, HGS refers to the test administrator/main interlocutor. A research assistant (AS) was also present, but she contributed mainly with minimal responses.

¹³ For a more thorough analysis of this extract, see Svennevig & Lind (2016).

¹⁴ Unfortunately, sentence repetition was not tested, so this important diagnostic feature remains unattested.

¹⁵ The texts are segmented into AS-units (analysis of speech units) (Foster, Tonkyn, & Wigglesworth, 2000) divided by extra interlinear space in the transcription. The relevant key concept components (cf. Table 2) are marked by numbered boxes. Utterances in the non-target language are italicised. Three dots indicate pauses, unintelligible utterances are marked by X and X= , and uncertain interpretations are indicated by brackets.

Additional information

Funding

This work was supported by The Research Council of Norway [223265 and 250093].