Protective factors, risk factors, and intervention strategies in the prevention and reduction of crime among adolescents and young adults aged 12–24 years: A scoping review protocol
Notice bibliographique
Résumé
BACKGROUND: Evidence indicates that criminal behaviour in youth is linked with a range of negative physical, mental, and social health consequences. Despite a global decrease over the last 30 years, youth crime remains prevalent. Identifying and mapping the most robust risk and protective factors, and intervention strategies for youth crime could offer important keys for predicting future offense outcomes and assist in developing effective preventive and early intervention strategies. Current reviews in the area do not include literature discussing at risk populations such as First Nations groups from countries such as Australia, Canada and New Zealand. This is a critical gap given the disproportionally high rates of incarceration and youth detention among First Nations people globally, particularly in countries with a colonial past. The aim of this scoping review is to identify and map the key risk and protective factors, along with intervention strategies, that are essential for recognizing adolescents and young adults at risk of crime. METHODS: This scoping review protocol has been developed in line with the Arksey and O'Malley framework and the Joanna Briggs Institute (JBI) Reviewers' Manual. The review protocol was preregistered with Open Science Framework (https://osf.io/kg4q3). ProQuest, PubMed, Web of Science, Scopus, and PsycInfo were used to retrieve relevant articles. Grey literature was searched using Google searches and ProQuest dissertations databases. Original research articles examining protective factors, risk factors, and intervention strategies for prevention and reduction of crime in 12-24-year-olds were included. Two independent reviewers conducted eligibility decisions and data extraction. Findings has been reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews. CONCLUSION: Anticipated findings suggest that current research has extensively examined factors across all levels of the socioecological model, from individual to community levels, revealing a predominant focus on individual-level predictors such as substance use, prior criminal history, and moral development. The review is expected to identify effective interventions that address critical factors within each domain, including Multisystemic Therapy (MST) and Multidimensional Treatment Foster Care (MTFC), which have shown promise in reducing youth crime. Additionally, it will likely highlight significant trends in risk and protective factors, such as the dual role of academic achievement-both as a risk and protective factor-and the impact of family-based interventions. The review will also address gaps in research, particularly regarding Indigenous youth, underscoring the need for targeted studies to better understand their unique challenges. These findings will guide future research and inform the development of comprehensive prevention and early intervention programs tailored to diverse youth populations.
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 | 0,090 | 0,101 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,004 |
| Méta-épidémiologie (sens large) | 0,012 | 0,016 |
| Bibliométrie | 0,020 | 0,015 |
| Études des sciences et des technologies | 0,005 | 0,004 |
| Communication savante | 0,009 | 0,007 |
| Science ouverte | 0,006 | 0,008 |
| Intégrité de la recherche | 0,009 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,049 | 0,009 |
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 ».