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Enregistrement W4293764522 · doi:10.1111/1460-6984.12776

Stability of language difficulties among a clinical sample of preschoolers

2022· article· en· W4293764522 sur OpenAlexafffundabout
Chantale Breault, Marie‐Julie Béliveau, Fannie Labelle, Florence Valade, Natacha Trudeau

Notice bibliographique

RevueInternational Journal of Language & Communication Disorders · 2022
Typearticle
Langueen
DomainePsychology
ThématiqueLanguage Development and Disorders
Établissements canadiensCentre Hospitalier Universitaire Sainte-JustineUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalCentre for Interdisciplinary Research in Rehabilitation
Organismes subventionnairesSocial Sciences and Humanities Research Council of Canada
Mots-clésMcNemar's testPsychologyPersistence (discontinuity)Test (biology)El NiñoPediatricsDevelopmental psychologyLanguage developmentMedicine

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Some data call into question the persistence of developmental language disorders (DLDs) identified during the preschool period. For this reason, speech-language pathologists (SLPs) often reassess children. However, it is unclear if the instability of the profiles documented in community sample studies is present in children referred to specialized clinics. Given the scarcity of SLP resources, is re-evaluating the language skills of these children a good use of clinical time? AIM: To examine the stability of the findings from two SLP assessments in a sample of Canadian preschool children referred to a tertiary clinic between the ages of 2 and 6 years. It was hypothesized that children under the age of 4 years at first assessment and children with less severe initial deficits would show less stability of DLD diagnosis. METHODS & PROCEDURES: The clinical files of children referred to an early childhood psychiatric clinic in Canada were reviewed. For 149 children with two SLPs assessment reports, persistence of language deficits was documented and tested with McNemar's statistics. Differences between preschoolers under the age of 4 versus 4 years and over, as well as between mildly and severely impaired children, were examined. OUTCOMES & RESULTS: High level of agreement (94%) and McNemar's test (p = 0.180) supported the stability of initial diagnosis. The stability for children assessed before the age of 4 (n = 64) was 100%, and was significantly different from older children's (n = 85) stability of 89% (Fisher's exact test, p = 0.01; bilateral). The stability for children with mild impairments (n = 18) was 78%, which was significantly lower than the stability (97%) in children with severe impairments (n = 114) (Fisher's exact test, p = 0.007; bilateral). CONCLUSIONS & IMPLICATIONS: No instability of language status was observed in children assessed before 4 years of age, which could be related to the significant severity of the difficulties that children in this age group presented and be specific to this type of clinical sample. The great stability of language status observed in preschoolers referred to a specialized clinic suggests that clinicians should limit reassessments to devote available resources to intervention efforts. WHAT THIS PAPER ADDS: What is already known on this subject? Previous research that has demonstrated important instability in the classification of language impairment before 4 years of age gathered data mainly by screening the general population or was not based on a comprehensive clinical assessment. What this paper adds to existing knowledge? This study investigated the classification stability of DLD between two comprehensive SLP assessments in a clinical sample of Canadian preschoolers. The results indicate great stability of language status assessed before 4 years old in this population, suggesting that severity of impairments may trump the age factor in this group. What are the potential or actual clinical implications of this work? In the case of children referred to a specialized clinic, clinicians and policymakers should be aware that DLD diagnosis made before 4 years of age remains stable during preschool age, and that a best practice with this population would be to abandon unnecessary testing in favour of early intervention.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,234
Score d'incertitude au seuil0,996

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0020,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0050,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,026
Tête enseignante GPT0,361
Écart entre enseignants0,335 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2022
Routes d'admission3
Résumé présentoui

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