The mental health of Indigenous Peoples during the COVID-19 pandemic: A scoping review
Bibliographic record
Abstract
Indigenous Peoples face significant disparities related to mental health and well-being due to colonization and its ongoing impacts, further impacted by COVID-19. Following Arksey and O’Malley’s six-stage framework and Bartlett’s Indigenous Two-Eyed Seeing approach, a reflexive review of the literature about Indigenous mental health during the pandemic was undertaken. Consultant interviews were also completed, and thematically organized, with Indigenous People from three Indigenous-serving mental health organizations in Ontario. Key themes included: highlighting Indigenous voices, historical context, challenges and strengths in culturally based services, virtual transition, financial support for Indigenous services, health service delivery and well-being, and culture and community connection. The themes bridge gaps in service provision, the mental health impacts of loss of connection with community due to pandemic restrictions, how mental health supports can be improved, and which services provided during the pandemic should continue. This review provides service providers clear recommendations based on the findings to help improve Indigenous mental health and service provision.
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 | 0.018 | 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 | 0.028 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".