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Enregistrement W2764888884 · doi:10.1542/peds.2010-3605

Preliteracy Intervention: Lessons to be Learned From Seemingly Discrepant Results

2011· letter· en· W2764888884 sur OpenAlexaboutno aff
James Law

Notice bibliographique

RevuePEDIATRICS · 2011
Typeletter
Langueen
DomaineMedicine
ThématiqueAttention Deficit Hyperactivity Disorder
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésIntervention (counseling)DisadvantageMedicinePsychological interventionValue (mathematics)Face (sociological concept)LiteracyWork (physics)Medical educationDevelopmental psychologyPsychologyPedagogyNursingSocial science

Résumé

récupéré en direct d'OpenAlex

At face value, promoting early literacy skills is a bit of a “no-brainer.” We all want to maximize the life opportunities for children, and early intervention is immensely appealing for parents, practitioners, and policy-makers alike. Early intervention is increasingly supported by neurobiological evidence for the negative consequences of restricted environments1 and the economic evidence for the value of early intervention.2 Yet, knowing that early intervention has been shown to work for one aspect of development at a given age and dosage is not the same as saying that such results will be universally applicable. Indeed, as the 2 studies discussed in this issue of Pediatrics demonstrate,3,4 the results of effectiveness studies may seem contradictory; in this case, results of 1 study indicate that a preliteracy intervention does not work, and results of the other study indicate that it does. The research community has the responsibility of teasing these issues apart: how much does it work and for whom?The differences between the programs in question are instructive in helping to take the science of early intervention forward. At face value, the interventions themselves, “Let's Read” and “Little By Little,” a development of “Reach Out and Read,” are comparable in that they used nonspecialists to target preliteracy skills, although aspects of the delivery (location, intensity, and duration) differed. The study designs differed too. The Australian study3 used a conventional prospective design with details of allocation and statistical power. The sample came from “relative disadvantage,” although 80% of the parents concerned had more than 12 years of education. The US study,4 by contrast, randomly assigned subjects from a large existing database of children specifically identified because they are socially disadvantaged. In particular, the parents of their Spanish-speaking participants had the lowest educational level but their children responded most dramatically to the intervention.At face value, the US study seems to deliver more bang for its buck, but care should be taken not to overinterpret the results. Even if we assume that there were no systematic biases to distort the findings, it would seem that the Australian study specifically excluded those who the US study's results suggest are most likely to respond positively to the intervention. In both studies the authors controlled for various factors in accounting for their results, and it is clearly important to examine whether the effects of an intervention are direct or work through a third factor such as the child's communication environment. Similarly, the models may need to be expanded to better capture both parental characteristics such as motivation and mental health5 and child characteristics such as tested, rather than parental report of, IQ and language development.Finally, the results of these studies highlight the interesting tension between targeted and universal interventions in relation to the demographic characteristics of the populations concerned. It has been suggested that the relationship of preschool achievement to social disadvantage may be closely associated with the level of income inequality in the country concerned; such inequalities are more pronounced in the United States and the United Kingdom than they are in Australia or Canada.6 It may be that this type of intervention works better in the most disadvantaged populations, which rather suggests that universal interventions may not be the way forward for 2 seemingly contradictory reasons. On the one hand, there is a tendency for them to exacerbate health inequalities because those least in need of the messages may respond to the intervention more readily.7 On the other hand, care needs to be taken to ensure that the parents are not already using the intervention strategies of their own volition. It is important to go beyond oversimplistic notions of whether an intervention does or does not work to explore why such putatively similar interventions achieve such divergent results.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,348
score de la tête « metaresearch » (Gemma)0,525
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,348
Score d'incertitude au seuil0,804

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,3480,525
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0090,004
Bibliométrie0,0080,006
Études des sciences et des technologies0,0020,009
Communication savante0,0110,017
Science ouverte0,0160,009
Intégrité de la recherche0,0100,013
Charge utile insuffisante (le modèle a refusé de juger)0,0070,002

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 Opus0,125
Tête enseignante GPT0,359
Écart entre enseignants0,233 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

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

En bref

Citations3
Publié2011
Routes d'admission1
Résumé présentoui

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