Identifying and Taking Action on the Protective and Risk Factors of Black Maternal Mental Health: Protocol for Community-Based Participatory Study
Bibliographic record
Abstract
BACKGROUND: Maternal mental health disorders are associated with adverse maternal and infant health outcomes. Despite advances in screening and treatment, disparities in maternal mental health disorders continue to disproportionately affect Black mothers and birthing persons. While there are studies that have examined maternal mental health, a gap in research remains in understanding the protective and risk factors of Black maternal mental health in Canada. Identifying the risks and protective factors is critical for advancing equitable and inclusive policies and practices that promote maternal well-being and optimal outcomes for Black perinatal populations. OBJECTIVE: This paper presents an outline of a study protocol that seeks to identify the protective and risk factors of Black maternal mental health and to engage Black mothers and birthing persons from the Greater Toronto Area in codesigning a culturally safe and inclusive best practices model to inform policy and interventions. METHODS: The proposed study will use an exploratory 3-phase sequential mixed methods approach underpinned by the principles of health equity and community-based participatory research. Phase 1 will involve engaging Black mothers and birth persons (n=300) in a survey to examine the psychosocial determinants of Black maternal mental health, including depression, anxiety, discrimination, strong Black women trope, attitude toward seeking mental health, support, and stigma. In phase 2, we will conduct 6 focus groups and individual interviews (n=60) to explore the stressors in the context of Black mothers and birth persons' everyday lives, psychosocial and support needs, and conditions that promote their resilience. Finally, phase 3 will engage Black women and birthing persons (n=30) in a codesign session using the concept mapping method to identify priority areas for action to inform policy and programming. We will use SPSS version 26 (IBM Corp) to analyze the survey data, drawing on both descriptive and inferential statistics. NVivo (Lumivero), a qualitative data analysis software, will be used to organize the data from phase 2 into meaningful themes informed by Braun and Clarke's thematic analysis approach. RESULTS: Ethics approval was granted in July 2024. Data collection for phase 1 started in December 2024 and will be completed in April 2025. Findings from phase 1 will inform phases 2 and 3 of this study, which will be conducted in the third quarter of 2025. We will disseminate the results of this study in the second and third quarters of 2025. CONCLUSIONS: The findings will generate the much-needed knowledge to shift policy, practice, and research and support capacity building among Black mothers and birthing persons. In addition, the proposed study will contribute to informing policy initiatives and interventions at the health system and community level to advance mental health equity and build capacity among service providers to provide culturally safe and equitable mental health care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/70076.
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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 | 0.113 | 0.076 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.067 | 0.015 |
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".