Understanding Neighborhoods’ Impact on Youth Substance Use and Mental Health Outcomes in Paterson, New Jersey: Protocol for a Community-Based Participatory Research Study
Notice bibliographique
Résumé
BACKGROUND: Substance use among youth is a major public health concern. Of note, substance use among youth is increasing in prevalence, and the incidence of substance use at earlier ages is rising. Given the long-term consequences of early substance use, it is important to identify factors that increase youth vulnerability to drug use, as they may be important targets for future interventions. OBJECTIVE: This study aims to use innovative methods, such as venue-based sampling, to recruit youth who are disconnected from school and use community-based participatory research to gain a better understanding of the prevalence of substance use and important correlates among youth aged between 13 and 21 years in Paterson, New Jersey, a low-income, urban community. The study will use a convergent, mixed methods design involving multiple data collection components and the analysis of a ministrative data source, designed with the strengths of complex intervention frameworks in mind. The overall aims of the study are to identify the prevalence of substance use among youth who are engaged in school and not engaged in school; to understand important antecedents and correlates of substance use; and to use this information to inform social, environmental, and culturally appropriate interventions to address substance use and its correlates among youths in a lower-resourced urban community. METHODS: This study will use both qualitative and quantitative methods to address important questions. Specifically, semistructured interviews using focus group and interview methodologies will be used to assess youths' lived experiences and will account for specific details that quantitative methods may not be able to attain. In addition, quantitative methods will be used to examine direct and multilevel associations between neighborhood factors and youth substance use and mental health outcomes. RESULTS: A previous analysis from a substance use initiative in Paterson, New Jersey found that youth who use substances such as marijuana and alcohol are more likely to have higher rates of depression and anxiety. On the basis of the research questions, this study will examine the association between neighborhood characteristics, substance use, and mental health symptoms among youth in Paterson by using quantitative and qualitative methods and will use these findings to inform the adaptation of a community- and evidence-based substance use prevention intervention for these youths. CONCLUSIONS: The findings of this study will provide an important contribution to understanding the role of socioecological factors in predicting substance use and mental health outcomes among youth in a lower-resourced, urban community. Furthermore, these findings will serve as evidence for the development of a culturally informed, community-based prevention program to address substance use disparities for youth, including those who are truant in Paterson, New Jersey. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/29427.
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 | 0,073 | 0,039 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,004 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,004 | 0,003 |
| Études des sciences et des technologies | 0,009 | 0,003 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,005 | 0,005 |
| Intégrité de la recherche | 0,005 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,048 | 0,006 |
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 ».