Mental Health Services for American Indians and Alaska Natives: Need, Use, and Barriers to Effective Care
Bibliographic record
Abstract
This special review summarizes and illustrates the state of our knowledge regarding the mental health needs of American Indians and Alaska Natives. These needs are considerable and pervasive. The discussion begins by reflecting on the limits of psychiatric nomenclature and conceptual frameworks for revealing Native constructions of mental health and mental illness. The experience and manifestation of psychopathology can be both different and the same across cultures, hinging upon the extent to which such basic assumptions as the relationship of mind to body--and spirit in the case of Native people--or the primacy of the individual or social collective are shared. Having set the stage, this paper moves to recent empirical evidence regarding the mental health needs of American Indians and Alaska Natives: we review that evidence and consider it within the broader context of available services. The report closes with a brief overview of the most pressing issues and forces for change afoot in Indian country in the US. Most have to do with the structure and financing of care as tribes and other Native community-based organizations seek to balance self-determination and resource management to arrive at effective, fiscally responsible, culturally informed prevention, treatment, and aftercare options for their members. These changes may herald similar trends among First Nations people to the immediate north.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".