Trauma and Substance Use among Indigenous Peoples of the United States and Canada: A Scoping Review
Bibliographic record
Abstract
Substance use has been identified by Indigenous populations as contributing to health disparities facing their communities. Rates of trauma exposure and post-traumatic stress disorder are higher in Indigenous, compared to non-Indigenous, populations and have been linked to substance use. Historical trauma is thought to be one mechanism underlying substance use and related disorders. The purpose of the present study is to summarize the current state of the literature focusing on the association between trauma (historical and lived) and substance use among Indigenous populations in the United States and Canada. Databases were systematically searched using the preferred reporting items for systematic reviews and meta-analyses statement. The search strategy initially yielded 4,026 articles. After exclusion of ineligible articles, 63 articles remained for synthesis. Results of the present review provide evidence for a positive link between substance use and both historical trauma (i.e., 86.4% of studies) and lived trauma (i.e., 84.7% of studies). Indigenous participants reported that historical trauma and pain related to loss of cultural identity contributed to substance use in their communities. Indigenous participants also consistently described an association between lived trauma and substance use. Despite heterogeneity among Indigenous communities, findings suggest a significant association between trauma and substance use across many different tribes and settings (e.g., reservation/reserve, rural/urban). Indigenous participants identified healing from trauma and reconnecting with culture as necessary components for reducing substance use and maintaining sobriety. With this, the development and implementation of interventions should partner with Indigenous communities in a manner that promotes and enhances cultural values for healing.
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 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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.018 | 0.026 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".