Families Preparing a New Generation: Adaptation of an Adolescent Substance Use Intervention for Burmese Refugee Families
Bibliographic record
Abstract
Refugees frequently experience histories of trauma and stress of acculturation, which place them at a high risk for mental health and substance use problems. Although recently arrived foreign-born youths report lower rates of substance use than their American peers, substance use rates for children in refugee families often increase as acculturation occurs. We describe the adaptation of the Familias: Preparando a la Nueva Generación (Families: Preparing the New Generation; FPNG) parenting skills curriculum to prevent adolescent substance use among Burmese refugee families. The adapted curriculum introduces parents of newly acculturating adolescents to the problem of substance use and teaches them how to effectively communicate with their children to target specific adolescent risk factors. We conducted a pilot study of 10 FPNG sessions with 14 Burmese mothers at an urban community center. Pretest and posttest data and fidelity measures were collected to assess the effects of the adapted curriculum and the pilot study. We describe these measures and present a 3-phase cultural adaptation process model that details the study’s background and plans for future intervention adaptations. We also discuss challenges in adaptation and implementation of the FPNG intervention with Burmese refugee communities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".