Enhancing Early Language Disorder Detection in Preschools: Evaluation and Future Directions for the Gades Platform
Notice bibliographique
Résumé
BACKGROUND: Language acquisition is a critical developmental milestone, with notable variability during the first 4 years of life. Developmental language disorder (DLD) often overlaps with other neurodevelopmental disorders or simple language delay (SLD), making early detection challenging, especially for primary caregivers. OBJECTIVE: We aimed to evaluate the effectiveness of the Gades platform, an adaptive screening tool that enables preschool teachers to identify potential language disorders without direct support from nursery school language therapists (NSLTs). METHODS: The study took place in a nursery school and an early childhood educational and psychopedagogical center in Madrid, Spain, involving 218 children aged 6 to 36 months, 24 preschool teachers, and 2 NSLTs. Initially, NSLTs conducted informational sessions to familiarize teachers with DLDs and how to identify them. Following this, the teachers used the Gades platform to conduct language screenings independently, without ongoing support from NSLTs. The Gades platform was enhanced to collect detailed profiles of each child and implemented an adaptive screening model tailored to account for variability in language development. This setup allowed preschool teachers, who are not language experts, to observe and assess language development effectively in natural, unsupervised educational environments. The study assessed the platform's utility in guiding teachers through these observations and its effectiveness in such settings. RESULTS: Gades identified language difficulties in 19.7% (43/218) of the children, with a higher prevalence in boys (29/218, 13.3%) than in girls (14/218, 6.4%). These challenges were most frequently observed in children aged 15 to 27 months. The platform demonstrated a high accuracy rate of 97.41%, with evaluators largely agreeing with its recommendations. Teachers also found Gades to be user friendly and a valuable tool for supporting language development observations in everyday educational settings. CONCLUSIONS: Gades demonstrates potential as a reliable and accessible tool for early detection of language disorders, empowering educators to identify DLD and SLD in the absence of NSLTs. However, further refinement of the platform is required to effectively differentiate between DLD and SLD. By integrating Gades into routine preschool assessments, educators can facilitate timely interventions, bridging gaps in early childhood education and therapy. TRIAL REGISTRATION: Pan-African Clinical Trial Registry (PACTR) PACTR202210657553944; https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=24051.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».