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Record W3188631329 · doi:10.1111/1460-6984.12660

Description of connected speech across different elicitation tasks in the logopenic variant of primary progressive aphasia

2021· article· en· W3188631329 on OpenAlexafffund
Monica Lavoie, Sandra E. Black, David F. Tang‐Wai, Naida L. Graham, Steven Stewart, Carol Léonard, Elizabeth Rochon

Bibliographic record

VenueInternational Journal of Language & Communication Disorders · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsToronto Western HospitalUniversity of OttawaOntario Brain InstituteSunnybrook Health Science CentreToronto Rehabilitation InstituteUniversity Health NetworkUniversity of TorontoHealth Sciences Centre
FundersCanadian Institutes of Health Research
KeywordsPrimary progressive aphasiaConnected speechPsychologySentenceAphasiaSpeech productionAgrammatismCognitive psychologyAudiologyLinguisticsNatural language processingComputer scienceMedicineDisease

Abstract

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BACKGROUND: Despite its importance, in-depth analysis of connected speech is often neglected in the diagnosis of primary progressive aphasia (PPA) - especially for the logopenic variant (lvPPA) for which unreliable differential diagnosis has been documented. Only a few studies have been conducted on this topic in lvPPA. AIMS: The aim of this study was to describe and compare lexico-semantic and morphosyntactic features of connected speech in participants with lvPPA, in comparison with healthy controls, using three different elicitation tasks (i.e., picture description, story narration and semi-structured interviews). In addition to a number of discourse features, we were particularly interested in the presence or absence of syntactic deficits in this PPA variant in line with recent findings. METHODS & PROCEDURES: A prospective group study was conducted to compare lvPPA participants (n = 13) to age- and education-matched healthy controls (n = 13). For each individual, connected speech was obtained using three tasks: (1) The Cookie Theft picture description; (2) Cinderella Story; (3) Topic-directed interview. Production on each task was recorded, transcribed and analysed according to the Quantitative Production Analysis (QPA) protocol, a tool developed by Berndt et al. (2000) for the analysis of sentence production in aphasia. Differences between lvPPA and healthy controls and among elicitation tasks were analysed using repeated measures multilevel mixed-effects regression, separately for each outcome. OUTCOMES & RESULTS: Four measures were significantly different between lvPPA participants and healthy controls across all elicitation tasks. Specifically, lvPPA participants produced a reduced proportion of open-class words, a higher proportion of verbs, a higher proportion of pronouns and fewer well-formed sentences. For these measures, the difference between lvPPA and healthy controls was consistent among elicitation tasks, except for the proportion of well-formed sentences, where the difference between the two groups was significantly greater in the story narration task than in the other tasks. CONCLUSIONS & IMPLICATIONS: Across elicitation tasks that used the same analysis protocol (i.e., QPA), a similar pattern of deficits in connected speech emerged in lvPPA patients. Importantly, the findings replicate previous studies, which used different elicitation tasks and analysis protocols. Especially in relation to the documented syntactic deficits, these findings provide implications for differential diagnosis in PPA. WHAT THIS PAPER ADDS: What is already known on the subject Connected speech analysis can provide an important contribution to the language assessment for the logopenic variant of primary progressive aphasia (lvPPA). However, only a few studies have been conducted with this population. What this paper adds to existing knowledge This study highlights differences between patients with lvPPA and healthy controls regarding the proportion of open-class words, nouns, verbs and well-formed sentences. What are the potential or actual clinical implications of this work? Importantly, our results highlight syntactic deficits in the same group of individuals with lvPPA, using the same analysis protocol and across various elicitation tasks, which has implications for differential diagnosis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.033
GPT teacher head0.336
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations24
Published2021
Admission routes2
Has abstractyes

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Same venueInternational Journal of Language & Communication DisordersSame topicNeurobiology of Language and BilingualismFrench-language works237,207