The Effects of Historical Trauma on the Health of Indigenous Communities in North America
Bibliographic record
Abstract
Indigenous people living in the United States and Canada experience much poorer health outcomes than other groups of people in the regions. In addition to facing higher prevalence of many health conditions that shorten overall life expectancy, many Native Americans face restricted access to health care. Limited access to care affected the Indigenous community’s health during the COVID-19 pandemic. Income level and socioeconomic status are perhaps the most powerful social determinant of health, affecting access not only to health care itself, but also to other basic needs like nutritious food and safe housing, that in turn affect health. This essay is a review of the literature exploring physical and mental health disparities among Native and Indigenous peoples in North America and the potential roots of these disparities in historical events that caused widespread and lasting trauma to Native American communities. Sections of this paper explore the historical, cultural, and intergenerational traumas that contribute to physical and mental health issues, while also referencing and describing health disparities, social determinants of health, and the effects of historical events, colonization, and prevailing Eurocentric views. Information referenced in this essay was collected using the program Ovid to search for relevant documents. Like many marginalized communities, Indigenous communities experience racist or prejudice-filled acts, including physical assaults and microaggressions or subtle discriminations, which are common in LGBTQIA+ communities and Black communities. Studies have shown that there are direct relationships between racism and mental health, along with physical health. This essay explores the connections between historical trauma and current poor health indicators among Native American populations while exploring Methods of Measuring Health Outcomes Associated with Historical Trauma and presenting a discussion that seeks to place the reviewed information into context, offer conclusions and suggest next steps to address public health needs.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".