5 The Relationship between National Paediatric Research Funding and Health Outcomes in Canada
Bibliographic record
Abstract
Abstract Introduction The Canadian Institutes of Health Research (CIHR) is Canada's federal funding agency for health research. CIHR invests approximately $1 billion each year to support health research. A recent cross-sectional analysis of 14,060 paediatric grants from the National Institutes of Health (NIH) showed that funding for paediatric research was correlated with level of disease burden, although certain conditions were identified as either over- or under-funded. Objectives The objective of this study was to determine the relationship between national paediatric research funding and health outcomes in Canada. Methods Health research grants (project, operating, foundation, team, and catalyst grants) related to paediatrics were identified annually for each of 6 financial years (2015-16 to 2020-21) through systematic keyword searches of CIHR’s research funding database. Two researchers extracted data on the disease or topic being studied, and coded each grant according to the top 50 causes of mortality, top 10 causes of hospitalization, and 8 well-being dimensions (as defined by the Canadian Index of Child and Youth Well-being). Inter-rater reliability was first established and then 20% of grants were double-coded and reviewed for consistency. Data were then used to summarize total annual funding for paediatric research and compared to paediatric health outcomes. Results A total of 1703 grants with total funding in the amount of $702,217,490 related to paediatric research were identified in the period between 2015-16 and 2020-21 ($74,944,445 in 2015-16, $87,447,167 in 2016-17, $103,754,359 in 2017-18, $124,277,052 in 2018-19, $132,734,406 in 2019-20, and $179,060,060 in 2020-21). A total of 248 abstracts (14.6% of all included grants) were identified as focused on one of the top 4 leading causes of paediatric mortality. These included accidents ($3,709,863), intentional self-harm (suicide) ($8,529,544), congenital malformations, deformations, and chromosomal anomalies ($30,230,136), and malignant neoplasms ($61,550,990). A total of 379 grant abstracts (22.3%) were identified as focused on a leading cause of paediatric hospitalization. These included disorders related to short gestation and low birth weight ($33,381,731), mood (affective) disorders ($32,236,327), anxiety disorders ($10,445,260), and other mental health disorders ($56,584,714). The top dimensions of well-being identified as being studied were “Feeling happy and respected” (218 grants, $78,315), “Feeling protected” (89 grants, $34,166,781), and “Feeling secure” (83 grants, $27,158,835). Conclusion This analysis indicates that there is general alignment of health research funding in Canada with paediatric mortality, hospitalization, and well-being indicators. Understanding paediatric research funding patterns can help inform prioritization of specific paediatric areas for future strategic funding.
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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 | 0.009 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.019 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".