Community-driven mental health priorities for immigrant youth in Alberta
Bibliographic record
Abstract
Background: Immigrant youth population is more susceptible to poor mental and overall health due to environmental factors, such as higher risks of poverty, trauma, displacement, and settlement period, learning a new language, adapting to a new culture, and a lack or loss of social supports. The overall goal of this project was to identify the research priorities of immigrant youth with lived experience of mental health concerns to guide research in mental health and inform health policy in a partnership with community organizations across Alberta, Canada. Methods: This patient-oriented research was designed based on the James Lind Alliance Priority Setting Partnership five steps: (1) creating a steering committee; (2) gathering uncertainties (questions which cannot be answered by existing research); (3) refining uncertainties through steering committee; (4) prioritization with immigrant youth via focus groups and with stakeholder involved in the care of immigrant youth through a nominal group technique; and (5) finalizing priority setting, report and dissemination. A steering committee was created with immigrant youth who self-identified with lived experience of mental health issues, leaders from immigrant communities (aged 18-25), researchers, non-profit organization leaders, and healthcare or community service providers. The electronic survey was distributed in rural, remote, suburban, and urban settings to recruit self-identified immigrant ("someone who has permanently located in a country other than their place of home origin") youth between the ages of 15 and 25 residing in Alberta, Canada. Results: Based on 148 responses from immigrant youth with a mental health concern, 25 uncertainties were refined. The top five priorities were chosen at the focus groups and NGT. Youth prioritized uncertainties related to them and their communities, while key informants emphasized higher-level uncertainties (resources, institutional barriers). Both prioritized community roles in reducing stigma, schools' role in addressing mental health, and the impact of COVID-related isolation. Conclusions: This study underscores the need for policies that support the tailoring of mental health services to the individual needs of immigrant youth. The findings from this study affirm that immigrant youth recognize mental health as not linear or universal; they seek to support each other and advocate for systemic changes that increase literacy and access to care.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".