Faculty Opinions recommendation of Indigenous mental health in a changing climate: a systematic scoping review of the global literature.
Bibliographic record
Abstract
Indigenous Peoples globally are among those who are most acutely experiencing the mental health impacts of climate change; however, little is known about the ways in which Indigenous Peoples globally experience climate-sensitive mental health impacts and outcomes, and how these experiences may vary depending on local socio-cultural contexts, geographical location, and regional variations in climate change. Thus, the goal of this study was to examine the extent, range, and nature of published research investigating the ways in which global Indigenous mental health is impacted by meteorological, seasonal, and climatic changes. Following a systematic scoping review protocol, three electronic databases were searched. To be included, articles had to be empirical research published since 2007 (i.e. since the Intergovernmental Panel on Climate Change’s Fourth Assessment Report); explicitly discuss Indigenous Peoples and describe factors related to climatic variables and mental health. Descriptive data from relevant articles were extracted, and the articles were thematically analyzed. Fifty articles were included for full review. Most primary research articles described research in Canada (38%), Australia (24%), and the United States of America (10%), with the number of articles increasing over time. Mental health outcomes such as strong emotional responses, suicide, depression, and anxiety were linked to changes in meteorological factors, seasonality, and exposure to both acute and chronic weather events. The literature also reported on the ways in which the emotional and psychological impacts of climate were connected to changing place attachment, disrupted cultural continuity, altered food security and systems, forced human mobility, and intangible loss and damages. This review highlights global considerations for Indigenous mental health in relation to climate change, which can support Indigenous-driven initiatives and decision-making to enhance mental wellness in a changing climate.
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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 | 0.019 | 0.137 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.013 | 0.021 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.170 | 0.029 |
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".