This funding opportunity will support the development of a learning health system (LHS) network in perinatal mental health. The LHS approach integrates research, data, and knowledge for continuous improvement in care to help ensure that the most effective treatments are consistently updated and implemented equitably across Canada. This approach would also enable the rapid translation of research findings into clinical and care practice, providing a mechanism for evaluating program impacts and improving equitable service delivery. Furthermore, this approach would ensure continuous improvement in efficiency and effectiveness of the processes of the LHS. The network is expected to develop an LHS by: (i) collecting and synthesizing data from real-world practice ('practice to data'), (ii) using that data to answer questions and generate new and useful knowledge ('data to knowledge'), and (iii) applying that knowledge to improve care to equitably meet the needs of people with lived/living experience (PWLLE), caregivers/families and communities served ('knowledge to practice'), which includes knowledge mobilization and implementation science; see Additional Information.
Excellent research and LHSs should incorporate open science practices that enable timely access and sharing of research findings, data, and other outputs, see Additional Information.
Perinatal mental health (PMH) is an area that has seen significant research and service delivery investment/advancement in recent years at the local and regional levels. Perinatal mental illness occurs during prenatal and postpartum periods and includes conditions such as depression, anxiety, and post-traumatic stress disorder (PTSD). If untreated, these conditions can have long-lasting effects, increasing the risk of chronic mental health issues for the parent and developmental challenges for the child. Despite the availability of evidence-based treatments, barriers such as stigma, lack of knowledge, and limited access to care—especially in rural areas—create a gap in treating individuals to full remission. Additionally, First Nations, Inuit, and Métis Peoples, racialized people, persons with disability, and those that identify as 2SLGBTQI+ face higher rates of perinatal mental illness, with even less access to appropriate care.
Across Canada, there are several specialized PMH programs located in academic centers that provide gold-standard care, including psychological and pharmacological treatment, but they are often burdened with long waitlists. Referrals depend on geographic location and primary care provider knowledge, creating an inequitable system. Timely intervention can prevent long-term negative outcomes and improve quality of life for both parent and child. Specialized programs are already collaborating on clinical guidelines and quality indicators for care, as well as engaging Indigenous experts for culturally safe care. However, despite these efforts, there remains a lack of an integrated, equitable system for timely access to perinatal mental health services. The ability to link programs and local networks to develop an LHS in PMH would improve health outcomes, health equity, service delivery, and cost. Additionally, an LHS would ensure proper integration of PWLLE and caregiver/family insights, which are key in PMH patient care.
Applicants are expected to ensure equitable access of diverse researchers, including First Nations, Inuit and Métis peoples, to opportunities available within the research team that will be established with program funding. This includes ensuring the research environment is supportive and any systemic barriers are addressed effectively and swiftly (see the Best Practices in Equity, Diversity and Inclusion in Research for guidance and examples of systemic barriers).
Applicants are expected to adopt data management best practices to enable reproducible science and to enable successful sharing across the network (e.g., the FAIR principles – Findable, Accessible, Interoperable, Reusable). Final data policies and procedures, for example data access procedures, are expected to be publicly available. See Additional Information for more details.
Research Areas
This funding opportunity will support a project relevant to the development of a pan-Canadian learning health system network in perinatal mental health (PMH).
Role and Contributions of Applicant Partners: CIHR recognizes that a broad range of partners may be relevant to this opportunity and it is expected that applicant(s) describe the role of all applicant partners and how/if they will contribute to research and research related activities. Any consideration of risk and/or conflict of interest should also be explained, as appropriate.
Funds Available
CIHR and partner(s) financial contributions for this initiative are subject to availability of funds. Should CIHR or partner(s) funding levels not be available or are decreased due to unforeseen circumstances, CIHR and partner(s) reserve the right to reduce, defer or suspend financial contributions to grants received as a result of this funding opportunity.
CIHR reviewers heavily weight methodological rigor, including:
Strong theoretical framework
Clear hypotheses or research questions
Robust study design
Adequate controls, power calculations, and statistics
Reproducibility & transparency practices
Clear milestones and contingency plans
Predictor: Methodological strength is the #1 determinant across all CIHR committees.
CIHR prioritizes research that benefits:
The health of people living in Canada
Canadian healthcare systems and policies
Vulnerable or underserved populations
Chronic disease burdens in Canadian demographics
Predictor: Clear articulation of Canadian relevance dramatically improves scores.
Successful CIHR proposals:
Have 2–3 well-defined aims
Present realistic deliverables within the grant period
Include detailed methodologies for each aim
Avoid overambitious or unfocused scope
Demonstrate precise timeline and project management
Predictor: Feasibility + clarity of approach = high reviewer confidence.
Reviewers value:
Publications relevant to the field
Prior successful funding
Expertise aligned to each aim
Multi-disciplinary teams (clinicians, statisticians, biomedical scientists, policy experts)
For early-career investigators: mentorship, protected time, and institutional support
Predictor: A well-matched, credible team is essential.
Highly competitive CIHR proposals commonly include:
Pilot experiments or feasibility data
Retrospective analyses
Early mechanistic insights
Proof-of-concept findings
For high-risk or exploratory programs, strong rationale can substitute, but evidence is still preferred.
Predictor: Preliminary data significantly boosts chances.
CIHR explicitly evaluates EDI in:
Team composition
Training environment
Research design (sex, gender, intersectionality, inclusive sampling)
Barriers to participation or recruitment
Engagement with under-represented or Indigenous populations
Predictor: Meaningful EDI integration is essential; weak EDI sections lower scores.
CIHR places high value on:
How findings will reach clinicians, policymakers, communities, or the public
Realistic KT activities (briefs, publications, engagement, partnerships)
Integrated knowledge translation when applicable (co-design with stakeholders)
Predictor: Strong KT plan with defined stakeholders and products.
High success when aligned with:
Indigenous health
Digital health & AI
Aging and dementia
Chronic disease (cancer, cardiovascular, neurological)
Rare disease
Implementation science
Mental health, substance use
Health system strengthening
Predictor: Direct strategic alignment increases competitiveness.
CIHR reviewers look for feasibility evidence:
Confirmed clinical recruitment sites
Existing cohort or biobank access
Computational / lab infrastructure
Letters of support verifying data access
Agreements for collaboration or sharing
Predictor: Proven resource availability reduces perceived risk.
Successful budgets:
Are lean and proportional to aims
Avoid unnecessary equipment or inflated salaries
Align with Canadian Tri-Council rules
Include justification for trainees, supplies, analyses
Predictor: A clear, efficient budget strengthens feasibility.
| Pitfall | Why It Hurts |
|---|---|
| Vague or overly ambitious aims | Feasibility concerns |
| Weak or missing preliminary data | Too speculative |
| Poor methodology or unclear analytic plan | Low rigor |
| Minimal relevance to Canadian health | Weak significance |
| Poor EDI integration | Fails mandatory criteria |
| No KT or weak dissemination plan | Low potential impact |
| Unclear roles of team members | Execution risk |
| Overinflated budget | Reviewer concerns |
For an application to be eligible, all the requirements stated below must be met and be clearly identified as such in the Participant Table (See How to Apply section):
Eligible Countries:
Sponsor Institute/Organizations: Canadian Institutes of Health Research
Sponsor Type: Corporate/Non-Profit
Address: 234 Laurier Ave West, Ottawa, ON K1A 0K9
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Feb 05, 2026
Feb 05, 2026
$4,371,425
6,000,000 CAD
Affiliation: Canadian Institutes of Health Research
Address: 234 Laurier Ave West, Ottawa, ON K1A 0K9
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