ArticleAnnals of dyslexia2023
The ReadFree tool for the identification of poor readers: a validation study based on a machine learning approach in monolingual and minority-language children.
Article in Annals of dyslexia, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07072104 (Longitudinal Assessment of Multidomain Reading-FREE Neurocognitive Markers for Early Detection of Developmental Dyslexia), which is not on this map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Longitudinal Assessment of Multidomain Reading-FREE Neurocognitive Markers for Early Detection of Developmental Dyslexia (FREE-DD)
Who cites it
1 citing paper in PubMed.
- Identifying the risk of dyslexia in bilingual children: The potential of language-dependent and language-independent tasks.Frontiers in psychology · 2022Article
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12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this study, we validated the "ReadFree tool", a computerised battery of 12 visual and auditory tasks developed to identify poor readers also in minority-language children (MLC). We tested the task-specific discriminant power on 142 Italian-monolingual participants (8-13 years old) divided into monolingual poor readers (N = 37) and good readers (N = 105) according to standardised Italian reading tests. The performances at the discriminant tasks of the "ReadFree tool" were entered into a classification and regression tree (CART) model to identify monolingual poor and good readers. The set of classification rules extracted from the CART model were applied to the MLC's performance and the ensuing classification was compared to the one based on standardised Italian reading tests. According to the CART model, auditory go-no/go (regular), RAN and Entrainment
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