Clinical research lags behind biomedical, populationbased health, and health services research at multiple levels
Bibliographic record
Abstract
PURPOSE: Concerns regarding a decline in clinical research have been raised internationally. In this study, research initiatives and competitiveness of investigators seeking funding for clinical research were compared with those for three other health research themes in Canada, namely, biomedical, population-based, and health services research. METHODS: A retrospective, multi-level descriptive study was conducted using administrative data from the Canadian Institutes for Health Research (CIHR) research grants program. Annual growth rates in numbers of proposals submitted since year 2000 (level I of comparison), success rates of submissions (level II), and growth rates in funding received since fiscal-year 1999-00 (level III) were compared across themes. RESULTS: Proposal submission (Level I): The average annual rate of growth in proposal submissions for biomedical, clinical, population-based and health services research was 11.8%, 6.3%, 105.0% and 43.2%, respectively. Success rate (Level II) was lower in clinical research (24%; P-value < 0.001) compared with biomedical (34%), population-based (29%), and health services (28%) research. Funding (Level III) grew at an average rate of 16.1% per year for biomedical, 28.2% for clinical, 65.9% for population-based, and 86.2% for health services research. However, the median amount funded for clinical projects (CAD $154,535) was less (P-value < 0.0001) than that for biomedical projects ($225,346). CONCLUSION: The overall growth of research activities in clinical theme was slower than with research in other themes-fewer proposals were submitted and lower proportion of submissions was successful. Smaller amounts of funding were received for clinical projects compared with biomedical projects, but a handful of large-scale clinical projects influenced the growth rate in funding for all clinical research. This report underscores the concern that multi-level problems plague clinical research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.147 | 0.156 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.022 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".