Inuit youths’ explanations of avoidance of formal mental health services and what should be done: results from interviews in two Nunavut communities
Bibliographic record
Abstract
In Nunavut, Inuit territory in Canada, young people have suicide rates nine times higher than the overall Canadian rates. However, mental health services struggle to reach young people. Regional suicide prevention organizations call for improved services and a better continuum of care. Yet little research has explored young people's experiences with the services currently available. As part of a larger study on resilience in Inuit youth, we asked them to explain their lack of use of mental health and suicide prevention services. The study was conducted in Arviat and Pangnirtung and followed the Inuit methodology Aajiiqatigiingniq Research Methodology (ARM), a cultural process for consensus building and solution-seeking compatible with a qualitative research approach. Advisory boards were created in each community. Interviews were conducted with thirty-one Inuit youths age 15 to 24. Data were analyzed by a thematic analysis. Young Inuit expressed a general discomfort with available services, including uneasiness with the health center and the way services are provided, they lacked information about services, lamented inadequate outreach methods and expressed a feeling of mistrust. Our findings support the value of several ongoing initiatives based upon cultural traditions, and may inform the continuum of care for suicide prevention .
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".