MétaCan
Menu
Retour à la cohorte
Enregistrement W1584617658 · doi:10.1016/s2214-109x(15)00031-5

Reducing school violence in Africa: learning from Uganda

2015· letter· en· W1584617658 sur OpenAlexaff
William Pickett, Frank J. Elgar

Notice bibliographique

RevueThe Lancet Global Health · 2015
Typeletter
Langueen
DomaineHealth Professions
ThématiqueChild and Adolescent Health
Établissements canadiensMcGill UniversityDouglas Mental Health University InstituteQueen's University
Organismes subventionnairesnon disponible
Mots-clésScopusConvention on the Rights of the ChildMedicineCluster randomised controlled trialHuman rightsFamily medicineIntervention (counseling)Medical educationNursingPolitical scienceMEDLINELaw

Résumé

récupéré en direct d'OpenAlex

Violence pervades the lives of children around the world. For too long, society has ignored child violence and failed to hold adult guardians to account for their traumatising actions towards children. The right to be protected from violence is guaranteed by the United Nations Convention on the Rights of the Child,1United NationsConvention on the rights of the child. United Nations, New York1989http://www.ohchr.org/EN/ProfessionalInterest/Pages/CRC.aspxGoogle Scholar and yet children in many countries are routinely exposed to physical attacks as victims or as bystanders. Moreover, even though children spend more time in school than in any other setting, robust evidence on the prevention of violence in schools outside North America is scarce. The community trial by Karen Devries and colleagues in The Lancet Global Health2Devries KM Knight L Child JC et al.The Good School Toolkit for reducing physical violence from school staff to primary school students: a cluster-randomised controlled trial in Uganda.Lancet Glob Health. 2015; 3: e378-e386Summary Full Text Full Text PDF Scopus (116) Google Scholar is therefore a bold and important initiative in the field of paediatric violence. The trial evaluated a complex behavioural intervention—the Good School Toolkit, designed by non-profit organisation Raising Voices—in 42 Ugandan schools.2Devries KM Knight L Child JC et al.The Good School Toolkit for reducing physical violence from school staff to primary school students: a cluster-randomised controlled trial in Uganda.Lancet Glob Health. 2015; 3: e378-e386Summary Full Text Full Text PDF Scopus (116) Google Scholar The need for such an intervention is stark. According to a recent UNICEF report on violence,3United Nations Children's FundHidden in plain sight: a statistical analysis of violence against children. UNICEF, New York2014http://www.unicef.org/publications/index_74865.htmlGoogle Scholar Uganda's child homicide rate is 10 per 100 000 annually—one of the highest in the world—with 36% of 13–15-year-olds having been in a physical fight during the past year and 54% of 15–19-year-olds having experienced physical violence since age 15 years. Anecdotal reports suggest that most students have experienced physical punishment at school at the hands of school staff, including caning and slapping.4Devries KM Allen E Child JC et al.The Good Schools Toolkit to prevent violence against children in Ugandan primary schools: study protocol for a cluster randomised controlled trial.Trials. 2013; 14: 232Crossref PubMed Scopus (34) Google Scholar Such experiences are shared equally between boys and girls and track strongly into adult life in experiences involving forced sexual acts and attitudes towards intimate partner violence and using physical discipline with children.3United Nations Children's FundHidden in plain sight: a statistical analysis of violence against children. UNICEF, New York2014http://www.unicef.org/publications/index_74865.htmlGoogle Scholar This randomised trial of the Good School Toolkit is important not only because of its aim—to reduce physical violence from school staff enacted on primary school children—but also because of its novelty and quality. It represents one of the few cluster-randomised controlled trials of its kind in any setting. Its objectives, study population, and methods were clear and transparent. Devries and colleagues carefully considered threats to both internal and external validity within their design and interpretation, as well as the implications of the trial findings for public health. The reach of the intervention and cooperation of the school communities, staff members, and student bodies were both excellent. Methods of follow-up and assessment conformed to the highest possible standards. Indeed, the study represents a model in terms of the conduct of a community-based trial in a school-based setting and sets a new standard for evidence in support of school-based interventions. Still, despite its impressive findings—a significantly lower rate of violence was reported in intervention schools relative to controls after 18 months (595/1921 [31·0%] vs 924/1899 [48·7%]; odds ratio 0·40, 95% CI 0·26–0·64, p<0·0001), with no apparent adverse effects of the intervention—an astute reader will observe that the total efficacy of the intervention is modest. Even after this rigorous school-based intervention, almost a third of primary school children in the intervention group of the trial still reported one or more episodes of physical violence in the past week. This is violence perpetrated by school staff—acts that in other jurisdictions and countries could lead to severe reprimands, dismissal, or even incarceration. 434 children were referred to child protective services over the course of the trial, representing one in nine trial participants. Another caveat is that, although the efficacy of the intervention is clear, its broader and long-term effects on acts of corporal punishment and other forms of violence within and outside of the school system remain unknown. Hopefully, further follow-up will show a sustained decline in reported physical violence in all settings among students assigned to the intervention, but this remains to be seen. Violence against children represents a quiet epidemic, and schools offer researchers a natural laboratory in which to measure and study its prevalence and many consequences for mental and physical health and academic outcomes. However, schools are just one context in which children are victimised. Interventions that are conducted over a short-term period might affect school cultures and experiences, but both their immediate and sustained impacts on violence in homes, workplaces, and neighborhoods remain uncertain and need further study. It is important to recognise that social and structural determinants of violence—poverty, gender discrimination and racism, socioeconomic inequalities, political unrest, untreated mental health problems, addictions, and other root causes—will persist despite the best efforts of schools to counteract them. The need remains for further research that focuses more broadly on such fundamental determinants. Still, Devries and colleagues2Devries KM Knight L Child JC et al.The Good School Toolkit for reducing physical violence from school staff to primary school students: a cluster-randomised controlled trial in Uganda.Lancet Glob Health. 2015; 3: e378-e386Summary Full Text Full Text PDF Scopus (116) Google Scholar are to be commended for their very courageous and timely work. With the resources and political will needed to include such programmes in education curricula, schools in Uganda and elsewhere are ideally situated for laying the roots of broader social change towards the elimination of violence against children. Efforts to address such acts and to change societal norms are needed not only to prevent unnecessary deaths and trauma in vulnerable populations, but also to buttress the social and economic development of entire nations. We declare no competing interests. The Good School Toolkit for reducing physical violence from school staff to primary school students: a cluster-randomised controlled trial in UgandaThe Good School Toolkit is an effective intervention to reduce violence against children from school staff in Ugandan primary schools. Full-Text PDF Open Access

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)0,004
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,040
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,013
Charge utile insuffisante (le modèle a refusé de juger)0,0000,001

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.

Tête enseignante Opus0,107
Tête enseignante GPT0,416
Écart entre enseignants0,309 · 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 tête enseignante, 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

Citations5
Publié2015
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueThe Lancet Global HealthMême sujetChild and Adolescent HealthTravaux en français237 207