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Record W4396770840 · doi:10.2196/55470

Brief Parent-Child Substance Use Education Intervention for Black Families in Urban Cities in New Jersey: Protocol for a Formative Study Design

2024· article· en· W4396770840 on OpenAlexvenueno aff
Ijeoma Opara, Kimberly Pierre, Sandy Cayo, Kammarauche Aneni, Catherine Mwai, Aaron Hogue, Sara J. Becker

Bibliographic record

VenueJMIR Research Protocols · 2024
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute on Drug AbuseNational Institutes of Health
KeywordsPsychological interventionPopulationFormative assessmentSubstance abuse preventionPsychologyIntervention (counseling)Substance useEnvironmental healthMedicineClinical psychologyPsychiatryPedagogy

Abstract

fetched live from OpenAlex

BACKGROUND: Substance use continues to remain a public health issue for youths in the United States. Black youths living in urban communities are at a heightened risk of poor outcomes associated with substance use and misuse due to exposure to stressors in their neighborhoods, racial discrimination, and lack of prevention education programs specifically targeting Black youths. Many Black youths, especially those who live in urban communities, do not have access to culturally tailored interventions, leaving a critical gap in prevention. Since family is a well-known protective factor against substance misuse for Black youths, it is essential to create sustainable and accessible programming that incorporates Black youths' and their families' voices to develop a suitable prevention program for them. OBJECTIVE: We aim to understand the cultural and environmental level factors that influence substance use among Black youths and develop a prevention program to increase parent-child substance use education among Black families. METHODS: This study will take place within urban cities in New Jersey such as Paterson and East Orange, New Jersey, which will be the main study sites. Both cities have a large population of Black youths and this study's team has strong ties with youths-serving organizations there. A formative, qualitative study will be conducted first. Using the first 3 steps of the ADAPT-ITT (Assessment, Decision, Adaptation, Production, Topical Experts, Integration, Training, and Testing) framework we begin the development of an intervention for Black families. Three aims will be described: aim 1, collect qualitative data from Black parents and youths aged 11-17 years from parent-child dyads (N=20) on the challenges, barriers, and facilitators to communicating about substance use; aim 2, adapt a selected evidence-based intervention for Black families and develop a family advisory board to guide the adaptation; and aim 3 assess the feasibility of the intervention through theater testing, involving the family and community advisory board. RESULTS: This study is part of a 2-year research pilot study award from the National Institutes of Drug Abuse. Data collection began in May 2023, and for aim 1, it is 95% complete. All aim 1 data collection is expected to be complete by December 30, 2023. Data analysis will immediately follow. Aim 2 activity will occur in spring 2024. Aim 3 activity may begin in fall 2024 and conclude in 2025. CONCLUSIONS: This study will be one of the few interventions that address substance use among youths and uses parents and families in urban communities as a protective factor within the program. We anticipate that the intervention will benefit Black youths not only in New Jersey but across the nation, working on building culturally appropriate, community-specific prevention education and building on strong families' relationships, resulting in a reduction of or delayed substance use. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/55470.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.050
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.018
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0020.002
Science and technology studies0.0070.003
Scholarly communication0.0030.003
Open science0.0050.003
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0500.007

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.353
GPT teacher head0.553
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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