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Enregistrement W2106563039 · doi:10.7202/004730ar

Incidence de l abus et la négligence envers les enfants : recension des écrits

2002· article· en· W2106563039 sur OpenAlexaffvenueabout
Marc Tourigny, Chantal Lavergne

Notice bibliographique

RevueCriminologie · 2002
Typearticle
Langueen
DomainePsychology
ThématiqueChild Abuse and Trauma
Établissements canadiensUniversité du Québec
Organismes subventionnairesnon disponible
Mots-clésIncidence (geometry)Psychological interventionPsychologyVariety (cybernetics)Inclusion (mineral)Sexual abusePhysical abuseMedicineSocial psychologyPoison controlInjury preventionPsychiatryMedical emergency

Résumé

récupéré en direct d'OpenAlex

The mistreatment of children has become a major social concern. The suffering of children occurs in a variety of forms: sexual, physical or emotional abuse, and negligence. Studies that examine the incidence of child mistreatment have become an indispensable tool in documenting its extent, as well as its diverse forms, the characteristics of its victims and their abusers, and their environments. Such knowledge is essential to forming social policies, organizing services, and developing interventions and clinical practices adapted to the needs of families affected by this problem. The purpose of this article is to update current knowledge with regard to the incidence of child mistreatment. Specifically, it intends to determine rates of specific forms of mistreatment, to examine the evolution of such rates in recent years, and to identify important methodological shortcomings of studies in this area in order to identify challenges that must be met to obtain a reliable measurement of the extent of child mistreatment. Four methods of data collection were used to locate publications presenting rates of incidence: a bibliographical search among major data banks, a review of current literature, research among the web-sites of relevant organizations, and personal contacts with researchers working in this field. Literature was selected according to specific criteria for inclusion; 24 relevant publications were identified, a number of which present incidence rates based on a number of data banks and covering several years. The results demonstrate a significant variation in incidence rates, not only the rates of reported mistreatment (prior to investigation by child protection services) but also the rates of confirmed mistreatment following assessment. Reporting rates varied from 5 to 72 children per 1000 in the community; the child victim rates varied from 2 to 110 children per 1000. More than half of the situations of mistreatment consisted of negligence, followed by physical abuse (about 20 %), sexual abuse (about 10 %) and emotional abuse (about 6 %). An examination of regional rates also demonstrated significant differences. In general, the rates of reported as well as confirmed incidents in the United States were two to three times higher than those in Australia or Quebec, but only minimally higher than rates in Ontario. Rates of negligence and sexual or physical abuse followed the same pattern, while rates of emotional abuse were divergent. Differences among rates may to some extent be explained by regional differences, but methodological differences among studies are also important. Studies based on data from child protection agencies report much lower rates than studies based on data collected from professionals working with abused children in the community. Finally, rates of reported incidents of child mistreatment and rates of confirmed reports have increased significantly during the last twenty years. According to child protection services' data, rates seem to have stabilized since the beginning of the 1990s. According to data provided by community professionals however, the rate of child mistreatment has increased consistently during this period, whatever the form of abuse considered. The discussion of results examines three aspects: first, factors that may explain significant rate variations; second, the stability of rates reported by child protection services compared with the consistent rate increase reported by community professionals; and finally, current methodological shortcomings and means of improving future research.

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,932
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
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 ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,002

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 Opus0,384
Tête enseignante GPT0,420
Écart entre enseignants0,037 · 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

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

Citations26
Publié2002
Routes d'admission3
Résumé présentoui

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