Community‐based models of alcohol and other drug support for First Nations peoples in Australia: A systematic review
Bibliographic record
Abstract
ISSUES: The transgenerational impacts of colonisation-inclusive of dispossession, intergenerational trauma, racism, social and economic exclusion and marginalisation-places First Nations peoples in Australia at significant risk of alcohol and other drug (AOD) use and its associated harms. However, knowledge and evidence supporting community-based AOD treatment for First Nations adults is limited. Therefore, this review aimed to examine the impact and acceptability of community-based models of AOD support for First Nations adults in Australia. APPROACH: A systematic search of the empirical literature from the past 20 years was conducted. KEY FINDINGS: Seventeen studies were included. Nine studies evaluated the program's impact on substance use and 10 studies assessed program acceptability (two studies evaluated both). Only three out of nine studies yielded a statistically significant reduction in substance use. Acceptable components included cultural safety, First Nations AOD workers, inclusion of family and kin, outreach and group support. Areas for improvement included greater focus on holistic wrap-around psychosocial support, increased local community participation and engagement, funding and breaking down silos. IMPLICATIONS: Culturally safe, holistic and integrated AOD outreach support led by First Nations peoples and organisations that involves local community members may support First Nations peoples experiencing AOD concerns. These findings may inform the (re)design and (re)development of community-based AOD services for First Nations peoples. CONCLUSION: There is a limited evidence-base for community-based AOD programs for First Nations peoples. First Nations-led research that is controlled by and co-produced with First Nations peoples is necessary to extend our understanding of community-based programs within First Nations 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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".