Mental Health Challenges for Recent African Immigrant Men in Alberta, Canada
Bibliographic record
Abstract
This qualitative study utilizes a hermeneutic phenomenological approach to explore the challenges faced by recent African immigrant men in Alberta during their settlement, how those challenges affect their mental health and daily life, and how they respond. Eight men were recruited, and semi-structured, in-depth interviews were conducted. The data was analyzed using Reflexive Thematic Analysis, guided by Critical Race Theory, Intersectionality, and Social Determinants of Health frameworks. The findings underscore the interconnected challenges of employment precarity, racial discrimination, identity redefinition, cultural expectations, loneliness, and transnational financial pressures. Masculinity norms, mental health stigma, and cultural perceptions of formal services shaped help-seeking. This study highlights the importance of intersectional, anti-racist, and culturally humble, relationship-centred social work practice that acknowledges the structural determinants of health and the protective roles of cultural identity, familial responsibility, and spirituality. Rather than pathologizing lower uptake of formal services, practitioners should prioritize relationship-based continuous care, integrate cultural conceptions of wellness, and collaborate with faith and community organizations as co-creators of care. Policy recommendations include enhanced system navigation support (digital, financial, and employment), reforms to credential recognition, and newcomer employment supports that address racialized institutional barriers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".