Exploring the contributions and suitability of relational and community‐centered fetal alcohol spectrum disorder (FASD) prevention work in First Nation communities
Bibliographic record
Abstract
BACKGROUND: This study provides initial evidence of the contributions and suitability of relational, trauma-informed, and community-based approaches for programs aimed at the prevention of future alcohol-and drug-exposed births. Specifically, this study extends understanding of the experiences of mentors providing evidence-based 3-year home visitation services through the Parent-Child Assistance Program (PCAP) in rural and isolated First Nation communities in Alberta, Canada. METHODS: Using a participatory approach to this research project, we explored existing PCAP services to capture implementation across six rural and isolated Alberta fetal alcohol spectrum disorder (FASD) networks involving First Nation communities over an 8-month period. In total, we generated qualitative data with 35 participants to examine mentors' perceptions of the impacts and suitability of a relational, trauma-informed, and community-based approach to service delivery. RESULTS: Six major themes were revealed from the thematic analysis as key mechanisms of culturally responsive program delivery across the six FASD networks. CONCLUSIONS: Relational, trauma-informed, and community-centered FASD prevention programming was perceived to have positive impacts and be well suited for use within Indigenous communities, and allow for service delivery to be locally and culturally responsive.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".