Evaluating a Digital Intervention to Reduce Aggression and Pro-Firearm Violence Attitudes Among Young Black Males: Pretest-Posttest Feasibility Study
Notice bibliographique
Résumé
Background: Pediatric and adolescent firearm injuries and fatalities in the United States have surged to levels not seen since the mid-1990s, marking a critical public health inflection point. Young Black males (ages 15-24) experience firearm-related fatality rates 24 times higher than their White peers. Despite this disproportionate risk, they are less likely to participate in traditional firearm violence prevention programs. This disparity highlights the urgent need for innovative, culturally responsive approaches that address the emotional, behavioral, and social determinants of violence. Objective: This pilot study aims to evaluate the preliminary effects of BrotherlyACT, a culturally responsive, trauma-informed, multicomponent mobile and web-based intervention designed to support young Black males (ages 15-24) in navigating and preventing community violence, substance use, and mental health challenges. The intervention aims to increase access to precrisis support and mental health resources for youth living in low-resource, high-violence settings. Methods: Seventy young Black males with Serious Fighting, Friend Weapon Carrying, Community Environment, and Firearm Threats (SaFETy) scores between 1 and 5 (indicating low-to-moderate firearm violence risk) were enrolled in this prospective pretest-posttest study. Participants completed a psychoeducational component of the BrotherlyACT intervention, consisting of 7 video-based modules. Surveys were administered at baseline and again 4 weeks later to assess changes in attitudes toward guns and violence (Attitudes Toward Guns and Violence Questionnaire), reactive and proactive aggression (Reactive-Proactive Aggression Questionnaire), psychological distress (Kessler Psychological Distress Scale), and depressive symptoms (8-item Patient Health Questionnaire). Paired t tests were conducted to analyze pre-post differences. Results: A total of 70 young Black males (mean age 20.97 years, SD 2.44 years) participated in the study. Nearly half reported recent physical fights (48/70, 69%), gun threats (39/70, 56%), or hearing gunshots in their neighborhood (63/70, 90%). More than 50% (39/70, 56%) reported illicit drug use, and 32 out of 70 (46%) reported substance-related violence. SaFETy scores revealed heterogeneous but elevated exposure to firearm risk factors, particularly in community violence and firearm threats. Postintervention, participants demonstrated a statistically significant reduction in attitudes toward guns and violence (Attitudes Toward Guns and Violence Questionnaire; mean 29.8-26.1, P<.001, d=0.53), with the largest shift observed in "Aggressive Response to Shame" (28% reduction). Reactive aggression significantly declined (mean 10.48-8.67, P=.008, d=0.37), whereas proactive aggression remained stable. Psychological distress and depressive symptoms remained stable. Nearly all participants (68/70, 97%) completed all modules in a single session, with 47 out of 70 (67%) finishing within an hour, suggesting high feasibility and user engagement. Conclusions: Preliminary findings indicate that BrotherlyACT may reduce proviolence attitudes and reactive aggression among young Black males. These results underscore the feasibility and potential impact of culturally responsive digital interventions as a strategy to prevent firearm violence among underserved 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 distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».