75 Can the Children’s Communication Checklist Differentiate Between Children with High Functioning Autism, ADHD, and Academically-Based Learning Disabilities?
Notice bibliographique
Résumé
Objective: The Children’s Communication Checklist-Second Edition (CCC-2) is a rating scale designed to assess domains of communication skills with emphasis on pragmatics (Bishop, 2006). The CCC comprises 10 subtests addressing various aspects of oral communication skills: Speech, Syntax, Semantics, Coherence, Initiation, Scripted Language, Context, Nonverbal Communication, Social Relations, and Interests. In a study conducted on the original CCC, Geurts et al. (2004) found that when compared to normal controls, pragmatic difficulties occurred in children with either high functioning autism (HFA) or ADHD. Since the initial version of the CCC, no study has examined whether the revised version can differentiate children with HFA, ADHD, and LD, the purpose of the present study. Focus was on derived factors of the structure/content of language and the pragmatics of language. Participants and Methods: Forty-one participants grouped according to diagnosis were drawn from two archival data pools, one adapted from a previous study conducted by Casey and Scott (2016) and the other from a set of anonymized patients from a neuropsychological clinic. Fourteen participants met clinical criteria for autism (Mage = 11.95), 12 participants met criteria for ADHD without co-morbid disorders (Mage = 9.5), and 15 participants met criteria for a learning disability involving reading, writing, math, or some combination (Mage = 10.13). Group-specific descriptive statistics were computed for the participants’ age, full scale intelligence quotient (IQ), and General Communication Composite (GCC). Two factor scores were computed, one composed of the subtests that constitute the structure/content aspects of language (Speech, Syntax, Semantics, and Coherence) and one composed of the pragmatic aspects of language (Initiation, Nonverbal Communication, Social Relations, and Interests), an area of particular weakness in HFA. Independent samples ANOVAs were conducted on both factor scores to determine whether the CCC-2 could differentiate the three groups. Post-hoc comparisons were planned for the subtests comprising the factor(s) that differentiated the groups. Results: Participants in the ADHD (M = 9.45, SD = 2.45) group were significantly younger than those in the HFA group (M = 11.95, SD = 2.24) and LD group (M = 10.13, SD = 2.58), the latter two not differing significantly. The groups did not differ significantly on IQ, nor on the structure/content factor. On the pragmatic factor, the LD group (M = 10.18, SD = 9.91) had significantly higher scores than the ADHD group (M = 7.79, SD = 6.54), which in turn, had significantly higher scores than the HFA group (M = 5.48, SD = 8.26), F(2, 38) = 17.81, p < .01. Within this composite, the same pattern was shown on Nonverbal Communication, F(2, 38) = 9.29, p < .01, and Interests, F(2, 38) = 17.81, p < .01. Conclusions: Compared to children with an academically-based learning disability, children with ADHD and HFA demonstrated pragmatic difficulties on the CCC-2. Although there was overlap between the pragmatic language characteristics of children with ADHD and children with HFA, the CCC-2 demonstrated utility in distinguishing the two disorders on certain aspects of communication skills, suggesting that it is a useful tool in differential diagnosis.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».