Recruitment Strategies to Engage Newcomer Mothers of African Descent in Maternal Mental Health Research in Canada
Bibliographic record
Abstract
INTRODUCTION: Newcomer mothers of African descent are at risk for maternal mental stress because of inadequate social support, newcomer status, and stress of motherhood. Limited participation of newcomer African mothers in mental health research contributes to a knowledge gap in this area further impacting culturally competent health services. This article reports recruitment strategies to better engage African newcomer women in maternal mental health research. METHODS: In-depth discussion of recruitment strategies, used in a qualitative descriptive study conducted with Black African newcomer mothers in Canada. RESULTS: Ten African newcomer mothers were successfully recruited using recruitment strategies such as engagement with religious organizations, snowballing, and the use of social media. DISCUSSION: Cultural beliefs on motherhood, resilience, and mental illness may account for hesitancy to engage in maternal mental health research. Recruitment strategies could help overcome the challenges and potentially diversify maternal mental health research in Canada through the engagement of African newcomer mothers.
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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 | 0.025 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".