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Sensitivity and Specificity of French Language and Processing Measures for the Identification of Primary Language Impairment at Age 5

2010· article· en· W2076480233 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Speech Language and Hearing Research · 2010
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineMcGill UniversityJewish Rehabilitation HospitalQuebec Rehabilitation Research NetworkMcGill University Health CentreCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsSpecific language impairmentPsychologySentenceCutoffVocabularyAudiologyLanguage developmentImitationGrammarLanguage delayLinguisticsDevelopmental psychologyArtificial intelligenceMedicineComputer science

Abstract

fetched live from OpenAlex

PURPOSE: Research on the diagnostic accuracy of different language measures has focused primarily on English. This study examined the sensitivity and specificity of a range of measures of language knowledge and language processing for the identification of primary language impairment (PLI) in French-speaking children. Because of the lack of well-documented language measures in French, it is difficult to accurately identify affected children, and thus research in this area is impeded. METHOD: The performance of 14 monolingual French-speaking children with confirmed, clinically identified PLI (M = 61.4 months of age, SD = 7.2 months) on a range of language and language processing measures was compared with the performance of 78 children with confirmed typical language development (M age = 58.9 months, SD = 5.7). These included evaluations of receptive vocabulary, receptive grammar, spontaneous language, narrative production, nonword repetition, sentence imitation, following directions, rapid automatized naming, and digit span. Sensitivity, specificity, and likelihood ratios were determined at 3 cutoff points: (a) -1 SD, (b) -1.28 SD, and (b) -2 SD below mean values. Receiver operator characteristic curves were used to identify the most accurate cutoff for each measure. RESULTS: Significant differences between the PLI and typical language development groups were found for the majority of the language measures, with moderate to large effect sizes. The measures differed in their sensitivity and specificity, as well as in which cutoff point provided the most accurate decision. Ideal cutoff points were in most cases between the mean and -1 SD. Sentence imitation and following directions appeared to be the most accurate measures. CONCLUSIONS: This study provides evidence that standardized measures of language and language processing provide accurate identification of PLI in French. The results are strikingly similar to previous results for English, suggesting that in spite of structural differences between the languages, PLI in both languages involves a generalized language delay across linguistic domains, which can be identified in a similar way using existing standardized measures.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.805
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.375
Teacher spread0.324 · 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