Trauma-informed Approaches to Substance Use Interventions with Indigenous Peoples: A Scoping Review
Bibliographic record
Abstract
Indigenous Peoples experience disproportionately higher rates of problematic substance use. These problems are situated in a context of individual and intergenerational trauma from colonization, residential schools, and racist and discriminatory practices, policies, and services. Therefore, substance use interventions need to adopt a trauma-informed approach. We aimed to synthesize and report the current literature exploring the intersection of trauma and substance use interventions for Indigenous Peoples. Fourteen databases were searched using keywords for Indigenous Peoples, trauma, and substance use. Of the 1373 sources identified, 117 met inclusion criteria. Literature on trauma and substance use with Indigenous Peoples has increased in the last 5 years (2012-2016, n = 29; 2017-2021, n = 48), with most literature coming from the United States and Canada and focusing on historical or intergenerational trauma. Few articles focused on intersectional identities such as 2SLGBTQIA+ (n = 4), and none focused on veterans. There were limited sources (n = 25) that reported specific interventions at the intersection of trauma and substance use. These sources advocate for multi-faceted, trauma-informed, and culturally safe interventions for use with Indigenous Peoples. This scoping review illuminates gaps in the literature and highlights a need for research reporting on trauma-informed interventions for substance use with Indigenous Peoples.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".