Exploring risk and protective factors for adolescent dating violence across the social-ecological model: A systematic scoping review of reviews
Notice bibliographique
Résumé
Background: Adolescent dating violence (ADV) is a serious issue that affects millions of youth worldwide. ADV can be any intentional psychological, emotional, physical, or sexual aggression that occurs in adolescent dating and/or sexual relationships, and can occur both in person and electronically. The mental health consequences of ADV can be significant and far reaching, with studies finding long-term effects of dating violence victimization in adolescence. Preventing ADV so that youth do not experience negative mental health consequences is thus necessary. To be effective, however, prevention efforts must be comprehensive and address more than one domain of the social-ecological model, incorporating risk and protective factors across the individual level; relationship level; community level; and societal level. To support researchers and practitioners in designing such prevention programs, an understanding of what risk and protective factors have been identified over the past several decades of ADV research, and how these factors are distributed across levels of the social-ecological model, is needed. Methods: This study was conducted in accordance with PRISMA guidelines. We included peer-reviewed articles published in English between January 2000 and September 2020. The search strategy was developed in collaboration with a research librarian. Covidence was used for title and abstract screening and full text review. Data were extracted from included articles using a standardized charting template, and then synthesized into tables by type of factor (risk or protective), role in ADV (victimization or perpetration), and level(s) of the social-ecological model (individual, relationship, community, societal). Results: Our initial search across six databases identified 4,798 potentially relevant articles for title and abstract review. Following title and abstract screening and full text review, we found 20 articles that were relevant to our study objective and that met inclusion criteria. Across these 20 articles, there was a disproportionate focus on risk factors at the individual and relationship levels of the social-ecological model, particularly for ADV perpetration. Very little was found about risk factors at the community or societal levels for ADV victimization or perpetration. Furthermore, a very small proportion of articles identified any protective factors, regardless of level of the social-ecological model. Conclusion: Despite best practice suggesting that ADV prevention strategies should be comprehensive and directed at multiple levels of an individual's social ecology, this systematic scoping review of reviews revealed that very little is known about risk factors beyond the individual and relationship level of the social-ecological model. Further, past research appears steeped in a risk-focused paradigm, given the limited focus on protective factors. Research is needed that identifies risk factors beyond the individual and relationship levels, and a strengths-based focus should be used to identify novel protective factors. In addition, a more critical approach to ADV research - to identify structural and not just individual risk and protective factors - is needed.
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 | 0,017 | 0,081 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,009 | 0,009 |
| Bibliométrie | 0,023 | 0,020 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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 ».